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Volume 14
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World Electr. Veh. J., Volume 14, Issue 1 (January 2023) – 25 articles

Cover Story (view full-size image): The development of autonomous battery electric vehicle concepts poses new challenges for the thermal management system. The computational power needed to enable autonomous vehicle operation results in high thermal loads. New interior designs with unconventional passenger arrangement and diverse use cases require changes to the heating, ventilation, and air conditioning (HVAC) system. Possible solutions include modified cooling system topologies, HVAC systems with novel sensors and control strategies, thermal comfort simulations, and thermoelectric heat pumps. These measures were implemented in the thermal management system of the collaboration project UNICARagil and are discussed in this paper. In the project funded by the Federal Ministry of Education and Research of Germany (BMBF), four autonomous battery electric vehicles are developed and built. View this paper
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13 pages, 2184 KiB  
Article
Review on Smart Charging of Electric Vehicles via Market-Based Incentives, Grid-Friendly and Grid-Compatible Measures
by Doris Johnsen, Lars Ostendorf, Mischa Bechberger and Daniel Strommenger
World Electr. Veh. J. 2023, 14(1), 25; https://doi.org/10.3390/wevj14010025 - 16 Jan 2023
Cited by 7 | Viewed by 4872
Abstract
Smart charging of electric vehicles is a promising concept for solving the current challenges faced by connecting mobility and electricity within the context of the ongoing sustainable energy transition. It allows cost savings for the expansion and operation of the power grid and [...] Read more.
Smart charging of electric vehicles is a promising concept for solving the current challenges faced by connecting mobility and electricity within the context of the ongoing sustainable energy transition. It allows cost savings for the expansion and operation of the power grid and a more efficient use of renewable energies. However, wide implementation of smart charging requires further work on technical and regulatory issues and further development of standards, especially an end-to-end consistency of the control signals. A fully automated process, as well as customisable services and flexible tariffs, would also facilitate wider market penetration. The novelty of this paper is the consensus of German pilot projects funded within the German programme “Elektro-Mobil” on the communication channel between all stakeholders for the use cases of smart charging based on market price incentives. Within this consensus, the projects have illustrated how specific standards can facilitate the communication between smart charging stakeholders, become a reality in the pilot projects and should be applied to further use cases in the low-voltage network. This consensus results in a white paper. On this basis, the adjustment of the standards can be made to ensure the consistency of the control signals from the beginning of the control process up to the end. In an advanced Edition, solutions for the prioritisation and orchestration of the different control signals could be designed. Full article
(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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<p>Smart charging system. Communication channels for price-driven use cases (green-coloured lines, upper graphic) and of emergency regulations via grid measures (red-coloured lines, lower graphic). In addition to the different communication channels in the respective use cases, the relevance of different standards depending on the use case is also shown.</p> Full article ">
20 pages, 2978 KiB  
Article
Fuel-Efficiency Improvement by Component-Size Optimization in Hybrid Electric Vehicles
by Swapnil Srivastava, Sanjay Kumar Maurya and Rajeev Kumar Chauhan
World Electr. Veh. J. 2023, 14(1), 24; https://doi.org/10.3390/wevj14010024 - 15 Jan 2023
Cited by 1 | Viewed by 2607
Abstract
Hybrid electric vehicles (HEV) play an important role in sustainable transportation systems. The component size of HEV plays a vital role in the fuel efficiency of vehicles. This paper presents a divided rectangle (DIRECT) method for component sizing of vehicles to ensure better [...] Read more.
Hybrid electric vehicles (HEV) play an important role in sustainable transportation systems. The component size of HEV plays a vital role in the fuel efficiency of vehicles. This paper presents a divided rectangle (DIRECT) method for component sizing of vehicles to ensure better fuel efficiency and satisfying drivability. A state–space model was used to represent the design problem. A constraint multi-input multi-output optimization problem was solved by our DIRECT optimization algorithm. Efficacy of the algorithm was tested with standard drive cycles, including drive cycles for Indian urban and highway conditions representing various driving scenarios in the country. The simulation results illustrated the effectiveness of the proposed algorithm. Full article
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<p>Architecture of parallel HEV.</p> Full article ">Figure 2
<p>Battery model.</p> Full article ">Figure 3
<p>Energy management scheme.</p> Full article ">Figure 4
<p>Hyper-rectangle formation in the DIRECT algorithm.</p> Full article ">Figure 5
<p>Identification of hyper-rectangles.</p> Full article ">Figure 6
<p>Design iterations.</p> Full article ">Figure 7
<p>Design variable before and after optimization.</p> Full article ">Figure 8
<p>Fuel efficiency comparison.</p> Full article ">Figure 9
<p>Pollutant emission comparison.</p> Full article ">Figure 10
<p>Energy usage (kJ) of HEV before optimization.</p> Full article ">Figure 11
<p>Energy usage (kJ) of HEV after optimization.</p> Full article ">Figure 12
<p>SOC and emissions before optimization.</p> Full article ">Figure 13
<p>SOC and emissions after optimization.</p> Full article ">
19 pages, 4507 KiB  
Article
The Role of Attitude, Travel-Related, and Socioeconomic Characteristics in Modal Shift to Shared Autonomous Vehicles with Ride Sharing
by Mahsa Aboutorabi Kashani, Mohammadhossein Abbasi, Amir Reza Mamdoohi and Grzegorz Sierpiński
World Electr. Veh. J. 2023, 14(1), 23; https://doi.org/10.3390/wevj14010023 - 14 Jan 2023
Cited by 10 | Viewed by 3467
Abstract
The integration of automation and shared mobility services would significantly affect transportation demand, especially mode choice. However, little is known about how attitudes, travel attributes, and demographic factors affect the modal shift to shared autonomous vehicles (SAVs). A stated preference survey was designed [...] Read more.
The integration of automation and shared mobility services would significantly affect transportation demand, especially mode choice. However, little is known about how attitudes, travel attributes, and demographic factors affect the modal shift to shared autonomous vehicles (SAVs). A stated preference survey was designed to determine the preferences of car and transit users in relation to a modal shift to SAVs. The binary logit models’ results revealed distinct behavior patterns and systematic heterogeneity among transit and private car users based on a representative sample of 607 individuals in 2021. The shifting behavior of both users is positively affected by attitudinal factors, including consumer innovativeness, perceived usefulness, sharing intention, and ecological awareness, while negatively affected by privacy concerns. In terms of travel-related attributes of SAVs, car users are eight times more sensitive to waiting times compared to transit users, who are three times more concerned with travel costs. Further, privacy concerns, the number of passengers sharing a trip, and the ratio of waiting time to travel time of SAVs were the major barriers to shifting the likelihood of car users’ behavior. In light of these findings, based on the likely effects of SAVs on shifting behavior, a number of practical implications are suggested for more effective policy making. Full article
(This article belongs to the Special Issue Feature Papers in World Electric Vehicle Journal in 2022)
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<p>Conceptual model framework for assessing the modal shift preference to SAVs with DRS.</p> Full article ">Figure 2
<p>Research methodology flowchart.</p> Full article ">Figure 3
<p>Frequency analysis of the modal shift preference to SAVs by (<b>a</b>) socio-economic characteristics and (<b>b</b>) travel-related factors.</p> Full article ">Figure A1
<p>The research questionnaire.</p> Full article ">
6 pages, 205 KiB  
Editorial
Acknowledgment to the Reviewers of World Electric Vehicle Journal in 2022
by WEVJ Editorial Office
World Electr. Veh. J. 2023, 14(1), 22; https://doi.org/10.3390/wevj14010022 - 13 Jan 2023
Viewed by 1680
Abstract
High-quality academic publishing is built on rigorous peer review [...] Full article
12 pages, 2377 KiB  
Article
Optimal Mileage of Electric Vehicles Considering Range Anxiety and Charging Times
by Xiuhong He and Yingying Hu
World Electr. Veh. J. 2023, 14(1), 21; https://doi.org/10.3390/wevj14010021 - 11 Jan 2023
Cited by 10 | Viewed by 3883
Abstract
This paper aims to find out the optimal mileage of battery electric vehicles (BEVs) by considering the trade-off between range anxiety and charging times, since frequent charging is a customary way to ease range anxiety for BEV drivers in practice, but declines the [...] Read more.
This paper aims to find out the optimal mileage of battery electric vehicles (BEVs) by considering the trade-off between range anxiety and charging times, since frequent charging is a customary way to ease range anxiety for BEV drivers in practice, but declines the life cycle of battery and increases the charging cost. We propose a power function to measure the range anxiety and then solve two types of optimal mileages. The results show that the increment of BEVs’ cruising range increases the optimal absolute mileage but decreases the optimal relative mileage, while the improvement of the driver’s tolerance to range anxiety increases both. It is concluded that improving the driver’s tolerance, such as by expanding charging infrastructures and raising drivers’ practical experience with BEVs, is more effective than the increment of BEVs’ cruising range. The findings help to understand the optimal mileage of EVs and provide recommendations on the design of BEVs’ cruising range. Full article
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<p>The plot of <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>A</mi> <mo stretchy="false">(</mo> <mi>x</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> at <span class="html-italic">Q</span> = 150, <span class="html-italic">n</span> = 1, …, 10.</p> Full article ">Figure 2
<p>The plot of <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>R</mi> <msub> <mi>A</mi> <mrow> <mn>0</mn> <mo>−</mo> <mn>1</mn> </mrow> </msub> <mo stretchy="false">(</mo> <mi>x</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> at <span class="html-italic">Q</span> = 150, <span class="html-italic">n</span> = 1, …, 10.</p> Full article ">Figure 3
<p>The plot of <math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mrow> <mn>0</mn> <mo>−</mo> <mn>1</mn> </mrow> </msub> <mo stretchy="false">(</mo> <mi>x</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> at <span class="html-italic">Q</span> = 150.</p> Full article ">Figure 4
<p>The plot of <math display="inline"><semantics> <mrow> <mi>T</mi> <mo stretchy="false">(</mo> <mi>x</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> at <span class="html-italic">Q</span> = 150, <span class="html-italic">n</span> = 5.</p> Full article ">Figure 5
<p>The optimal <span class="html-italic">x</span> under different cruising range scenarios.</p> Full article ">Figure 6
<p>The optimal <span class="html-italic">x</span> under different <span class="html-italic">n</span>.</p> Full article ">Figure 7
<p>The optimal <span class="html-italic">y</span> under different driving range scenarios.</p> Full article ">Figure 8
<p>The optimal <span class="html-italic">y</span> under different <span class="html-italic">n</span>.</p> Full article ">
17 pages, 3008 KiB  
Article
Fault Alarms and Power Performance in Hybrid Electric Vehicles Based on Hydraulic Technology
by Zhuan You
World Electr. Veh. J. 2023, 14(1), 20; https://doi.org/10.3390/wevj14010020 - 10 Jan 2023
Cited by 1 | Viewed by 1686
Abstract
In order to improve the fault alarm effect on the power performance of hydraulic hybrid electric vehicles (HEV), this paper proposes a fault alarm method for hybrid electric vehicle power performance based on hydraulic technology, builds a hybrid electric vehicle power system model, [...] Read more.
In order to improve the fault alarm effect on the power performance of hydraulic hybrid electric vehicles (HEV), this paper proposes a fault alarm method for hybrid electric vehicle power performance based on hydraulic technology, builds a hybrid electric vehicle power system model, uses hydraulic technology to extract the characteristic signals of key components, uses support vector mechanisms to build a hybrid electric vehicle classifier, and obtains the fault alarm results for dynamic performance based on hydraulic technology. The results show that the proposed method can improve real-time diagnosis and alarm for engine faults in HEV, and the fault can be diagnosed after 5 s of injection, thus ensuring the dynamic stability of HEV. Full article
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<p>Overall model structure of the power system of the hydraulic hybrid electric vehicle.</p> Full article ">Figure 2
<p>Velocity profile model.</p> Full article ">Figure 3
<p>Processing flow for characteristic signal data.</p> Full article ">Figure 4
<p>Structure diagram of the power performance fault alarm model of the hydraulic hybrid electric vehicle.</p> Full article ">Figure 5
<p>Power performance fault alarm process of the hydraulic hybrid electric vehicle.</p> Full article ">Figure 6
<p>Main experimental equipment. (<b>a</b>) transmission isolator, (<b>b</b>) Msensor, (<b>c</b>) magnetoelectric sensor, (<b>d</b>) engine, and (<b>e</b>) hydraulic pump/motor.</p> Full article ">Figure 7
<p>Experimental vehicle model.</p> Full article ">Figure 8
<p>Variation in driving speed and the remaining hydraulic energy of the hydraulic accumulator in the experimental vehicle model with and without faults. (<b>a</b>) Speed changes; (<b>b</b>) change in the remaining hydraulic energy of the hydraulic accumulator.</p> Full article ">Figure 9
<p>Real-time alarm results for the hydraulic accumulator’s internal resistance failure by the proposed method.</p> Full article ">Figure 10
<p>Changes in engine power and speed over time in experimental vehicle models with and without fault injection. (<b>a</b>) Engine power changes; (<b>b</b>) Engine speed changes.</p> Full article ">Figure 11
<p>Real-time alarm results for engine operation faults by the proposed method.</p> Full article ">Figure 12
<p>Real-time alarm results for hydraulic pump/motor faults by the proposed method.</p> Full article ">Figure 13
<p>Real−time alarm results for multi-type faults by the proposed method.</p> Full article ">Figure 14
<p>ROC curve of fault classification [<a href="#B10-wevj-14-00020" class="html-bibr">10</a>,<a href="#B11-wevj-14-00020" class="html-bibr">11</a>].</p> Full article ">Figure 15
<p>Root-mean-square error of fault classifications [<a href="#B10-wevj-14-00020" class="html-bibr">10</a>,<a href="#B11-wevj-14-00020" class="html-bibr">11</a>].</p> Full article ">
13 pages, 10966 KiB  
Article
Regenerative Braking Strategy of Dual-Motor EV Considering Energy Recovery and Brake Stability
by Tonglie Wu, Feng Wang and Peng Ye
World Electr. Veh. J. 2023, 14(1), 19; https://doi.org/10.3390/wevj14010019 - 9 Jan 2023
Cited by 13 | Viewed by 3669
Abstract
The dual-motor EV (Electric Vehicle) is increasingly favored by manufacturers for its excellent performance in terms of power and economy. How to further reduce its energy consumption and make full use of the dual-motor energy recovery is an important support to improve the [...] Read more.
The dual-motor EV (Electric Vehicle) is increasingly favored by manufacturers for its excellent performance in terms of power and economy. How to further reduce its energy consumption and make full use of the dual-motor energy recovery is an important support to improve the overall vehicle economy and realize the “dual carbon” strategy. For the dual-motor EV architecture, the motor model, power battery loss model and vehicle longitudinal braking force model are established and the energy recovery-dominated regenerative braking torque distribution (RBD) rule of the dual motors is designed. Based on genetic algorithm (GA) theory and taking into account SOC, vehicle speed and braking intensity, a regenerative-braking torque optimization method is proposed that integrates energy recovery and braking stability. The braking intensity of 0.3 and the initial vehicle speed of 90 km/h are selected for verification. Compared with the rule method, the energy recovery and stability are improved by 22.8% and 4.8%, respectively, under the genetic algorithm-based and energy recovery-dominated regenerative-braking torque distribution (GA-RBD) strategy. A variety of conditions are selected for further strategy validation and the result shows that compared with the rule-based method, both energy recovery and braking stability are improved as braking speed and braking intensity increase under the GA-RBD strategy. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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<p>Schematic diagram of an EV system structure.</p> Full article ">Figure 2
<p>Efficiency map of motor 1.</p> Full article ">Figure 3
<p>Efficiency map of motor 2.</p> Full article ">Figure 4
<p>Vehicle force analysis diagram of the braking process.</p> Full article ">Figure 5
<p>Regenerative braking torque distribution rules dominated by energy recovery.</p> Full article ">Figure 6
<p>GA-RBD distribution strategy architecture diagram.</p> Full article ">Figure 7
<p>Rules for setting weighting factors.</p> Full article ">Figure 8
<p>GA algorithm optimization process.</p> Full article ">Figure 9
<p>Vehicle speed-braking intensity-braking torque distribution maps. (<b>a</b>) Motor 1 braking torque. (<b>b</b>) Motor 2 braking torque. (<b>c</b>) Front wheel hydraulic braking torque. (<b>d</b>) Rear wheel hydraulic braking torque.</p> Full article ">Figure 9 Cont.
<p>Vehicle speed-braking intensity-braking torque distribution maps. (<b>a</b>) Motor 1 braking torque. (<b>b</b>) Motor 2 braking torque. (<b>c</b>) Front wheel hydraulic braking torque. (<b>d</b>) Rear wheel hydraulic braking torque.</p> Full article ">Figure 10
<p>Comparative graph of the different braking torque distribution strategies. (<b>a</b>) Motor 1 braking torque. (<b>b</b>) Motor 2 braking torque. (<b>c</b>) Front wheel hydraulic braking torque. (<b>d</b>) Rear wheel hydraulic braking torque.</p> Full article ">Figure 11
<p>Comparative graphs of motor efficiency under the different strategies. (<b>a</b>) Motor 1 efficiency. (<b>b</b>) Motor 2 efficiency.</p> Full article ">Figure 12
<p>Comparative graphs of energy recovery and stability under the different strategies. (<b>a</b>) Cumulative energy recovery. (<b>b</b>) Stability coefficient.</p> Full article ">
17 pages, 2458 KiB  
Article
Profitability Evaluation of Vehicle-to-Grid-Enabled Frequency Containment Reserve Services into the Business Models of the Core Participants of Electric Vehicle Charging Business Ecosystem
by Andrei Goncearuc, Nikolaos Sapountzoglou, Cedric De Cauwer, Thierry Coosemans, Maarten Messagie and Thomas Crispeels
World Electr. Veh. J. 2023, 14(1), 18; https://doi.org/10.3390/wevj14010018 - 6 Jan 2023
Cited by 4 | Viewed by 3392
Abstract
The current paper defines a framework for the introduction of frequency containment reserve (FCR) services, enabled by vehicle-to-grid (V2G) technology, into the business model of an entity owning and operating electric vehicle (EV) charging infrastructure. Moreover, the defined framework can also be extrapolated, [...] Read more.
The current paper defines a framework for the introduction of frequency containment reserve (FCR) services, enabled by vehicle-to-grid (V2G) technology, into the business model of an entity owning and operating electric vehicle (EV) charging infrastructure. Moreover, the defined framework can also be extrapolated, with minor adjustments, to the business models of different core participants of the EV charging business ecosystem. This study also investigates the financial factors impacted by this introduction, eventually evaluating its financial profitability under given assumptions and comparing it to the profitability of the traditional business model of an entity owning and operating a unidirectional EV charging infrastructure. The current research shows that offering additional V2G-enabled FCR services can be potentially more profitable than the existing unidirectional approach if the V2G technology reaches its maturity phase with mass market adoption and economies of scale. Full article
(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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<p>Business model: CPO + V2G (V2G—caused changes are marked in blue) [<a href="#B9-wevj-14-00018" class="html-bibr">9</a>].</p> Full article ">Figure 2
<p>Electricity price trendline (based on 2011–2021 data) for Belgian non-household users in function of consumption [<a href="#B47-wevj-14-00018" class="html-bibr">47</a>].</p> Full article ">Figure 3
<p>(<b>a</b>) EBIT of an entity owning a network of unidirectional EVSE in function of <span class="html-italic">Ny</span>; (<b>b</b>) EBIT of an entity owning a network of V2G EVSE in function of <span class="html-italic">Ny</span>.</p> Full article ">Figure 4
<p>(<b>a</b>) EBIT margin of an entity owning a network of unidirectional EVSE in function of <span class="html-italic">Ny</span>; (<b>b</b>) EBIT margin of an entity owning a network of V2G EVSE in function of <span class="html-italic">Ny</span>.</p> Full article ">Figure 5
<p>(<b>a</b>) EBITDA of entities owning a network of unidirectional and V2G EVSE in function of <span class="html-italic">Ny</span>; (<b>b</b>) EBITDA margins of entities owning a network of unidirectional and V2G EVSE in function of <span class="html-italic">Ny</span>.</p> Full article ">Figure 6
<p>ROI of entities owning a network of unidirectional and V2G EVSE in function.</p> Full article ">Figure 7
<p>EBIT (EUR) sensitivity to elected revenues and costs.</p> Full article ">
17 pages, 5419 KiB  
Article
The Suppression of Modular Multi-Level Converter Circulation Based on the PIR Virtual Impedance Strategy
by Chun Wang, Wenxu Yan, Wenyuan Wang, Hongyu Ni and Jie Chu
World Electr. Veh. J. 2023, 14(1), 17; https://doi.org/10.3390/wevj14010017 - 5 Jan 2023
Cited by 4 | Viewed by 2064
Abstract
In recent years, with the rise of the electric vehicle industry, there has been significant research on charging and power supply vehicle technologies for electric vehicles. In terms of the corresponding converter usage, modular multi-level converters (MMCs) are also increasingly used in the [...] Read more.
In recent years, with the rise of the electric vehicle industry, there has been significant research on charging and power supply vehicle technologies for electric vehicles. In terms of the corresponding converter usage, modular multi-level converters (MMCs) are also increasingly used in the field of electric vehicle power supply research because of their unique advantages. However, the circulating current problem of MMCs has not been effectively addressed in existing domestic and international studies. In this paper, we propose a proportional-integral resonant (PIR) control method combined with virtual impedance for the optimal suppression of the MMC internal circulating current problem based on the comparison and generalization of the existing methods. Based on the analysis of the working principle of MMCs, this paper proposes and adopts the control strategy of combining virtual impedance and proportional-integral resonance to suppress the circulating current and builds a simulation model in MATLAB to verify that the control strategy proposed in this paper is feasible. Full article
(This article belongs to the Topic Power Converters)
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<p>Typical MMC circuit structure.</p> Full article ">Figure 2
<p>MMC half-bridge submodule structure.</p> Full article ">Figure 3
<p>Working principle of an MMC half-bridge submodule. (<b>a</b>) Working condition in S = 1, i<sub>jk</sub> &gt; 0. (<b>b</b>) Working condition in S = 1, i<sub>jk</sub> &lt; 0. (<b>c</b>) Working condition in S = 0, i<sub>jk</sub> &gt; 0. (<b>d</b>) Working condition in S = 0, i<sub>jk</sub> &lt; 0.</p> Full article ">Figure 4
<p>MMC three-phase equivalent model.</p> Full article ">Figure 5
<p>Virtual impedance equivalence diagram.</p> Full article ">Figure 6
<p>Structural diagram of the PIR virtual impedance controller.</p> Full article ">Figure 7
<p>(<b>a</b>) Three−phase output voltage. (<b>b</b>) Three−phase output current.</p> Full article ">Figure 8
<p>(<b>a</b>) FFT analysis of the three−phase output voltage. (<b>b</b>) FFT analysis of the three−phase output current.</p> Full article ">Figure 9
<p>DC side’s current.</p> Full article ">Figure 10
<p>Modulated waves.</p> Full article ">Figure 11
<p>(<b>a</b>) Harmonic current without the suppressor. (<b>b</b>) FFT analysis of the bridge arm current without the suppressor.</p> Full article ">Figure 12
<p>(<b>a</b>) Harmonic current with the PI control suppressor. (<b>b</b>) FFT analysis of the bridge arm current with the PI control suppressor.</p> Full article ">Figure 12 Cont.
<p>(<b>a</b>) Harmonic current with the PI control suppressor. (<b>b</b>) FFT analysis of the bridge arm current with the PI control suppressor.</p> Full article ">Figure 13
<p>(<b>a</b>) Harmonic current with the QPR control suppressor. (<b>b</b>) FFT analysis of the bridge arm current with the QPR control suppressor.</p> Full article ">Figure 14
<p>(<b>a</b>) Harmonic current with the PIR virtual impedance composite suppressor. (<b>b</b>) FFT analysis of the bridge arm current with the PIR virtual impedance composite suppressor.</p> Full article ">
15 pages, 3704 KiB  
Article
Research on Active Collision Avoidance and Hysteresis Reduction of Intelligent Vehicle Based on Multi-Agent Coordinated Control System
by Chaochun Yuan, Yongfeng Lin, Jie Shen, Long Chen, Yingfeng Cai, Youguo He, Shuofeng Weng, Xinkai Wu, Yuqi Yuan, Yuxuan Gong and Qiuye Yu
World Electr. Veh. J. 2023, 14(1), 16; https://doi.org/10.3390/wevj14010016 - 5 Jan 2023
Cited by 7 | Viewed by 2605
Abstract
This paper provides a multi-agent coordinated control system to improve the real-time performance of intelligent vehicle active collision avoidance. At first, the functions and characteristics of longitudinal and lateral collision avoidance agents are analyzed, which are the main components of the multi-agent. Then, [...] Read more.
This paper provides a multi-agent coordinated control system to improve the real-time performance of intelligent vehicle active collision avoidance. At first, the functions and characteristics of longitudinal and lateral collision avoidance agents are analyzed, which are the main components of the multi-agent. Then, a coordinated solution mechanism of an intelligent vehicle collision avoidance system is established based on hierarchical control and blackboard model methods to provide a reasonable way to avoid collision in complex situations. The multi-agent coordinated control system can handle the conflict between the decisions of different agents according to the rules. Comparing with existing control strategies, the proposed system can realize multi decisions and planning at the same time; thus, it will reduce the operation time lag during active collision avoidance. Additionally, fuzzy sliding mode control theory is introduced to guarantee accurate path tracking in lateral collision avoidance. Finally, co-simulation of Carsim and Simulink are taken, and the results show that the real-time behavior of intelligent vehicle collision avoidance can be improved by 25% through the system proposed. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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<p>Diagram of vehicle force during braking.</p> Full article ">Figure 2
<p>Intelligent vehicle lateral collision avoidance route.</p> Full article ">Figure 3
<p>Topology of multi-agent coordinated control system.</p> Full article ">Figure 4
<p>Multi-agent coordinated control system based on blackboard model.</p> Full article ">Figure 5
<p>The choice of active collision avoidance during an emergency in different environments: (<b>a</b>) Dry asphalt pavement (μ = 0.8); (<b>b</b>) Wet asphalt pavement (μ = 0.5).</p> Full article ">Figure 6
<p>Active collision avoidance system control method: (<b>a</b>) Distributed coordinated control system; (<b>b</b>) Sequential control system.</p> Full article ">Figure 7
<p>Distributed multi-agent collision avoidance system simulation.</p> Full article ">Figure 8
<p>Simulation of longitudinal collision avoidance: (<b>a</b>) Vehicle speed; (<b>b</b>) Distance between vehicle and obstacle; (<b>c</b>) Brake pressure of the vehicles.</p> Full article ">Figure 9
<p>Simulation of lateral collision avoidance: (<b>a</b>) Lane-changing track; (<b>b</b>) Steering wheel angle; (<b>c</b>) Lane-changing track; (<b>d</b>) Lateral acceleration.</p> Full article ">
22 pages, 858 KiB  
Article
A Numerical Study of the Suitability of Phase-Change Materials for Battery Thermal Management in Flight Applications
by Daeyeun Kim, Saber Abdallahh, Gloria Bosi and Alastair Hales
World Electr. Veh. J. 2023, 14(1), 15; https://doi.org/10.3390/wevj14010015 - 5 Jan 2023
Cited by 3 | Viewed by 2343
Abstract
Battery pack specific energy, which can be enhanced by minimising the mass of the battery thermal management system (BTMS), is a limit on electric fixed-wing flight applications. In this paper, the use of phase-change materials (PCMs) for BTMSs is numerically explored in the [...] Read more.
Battery pack specific energy, which can be enhanced by minimising the mass of the battery thermal management system (BTMS), is a limit on electric fixed-wing flight applications. In this paper, the use of phase-change materials (PCMs) for BTMSs is numerically explored in the 3D domain, including an equivalent circuit battery model. A parametric study of PCM properties for effective thermal management is conducted for a typical one-hour flight. PCMs maintain an ideal operating temperature (288.15 K–308.15 K) throughout the entire battery pack. The PCM absorbs heat generated during takeoff, which is subsequently used to maintain cell temperature during the cruise phase of flight. In the control case (no BTMS), battery pack temperatures fall below the ideal operating range. We conduct a parametric study highlighting the insignificance of PCM thermal conductivity on BTMS performance, with negligible enhancement observed across the tested window (0.1–10 W m−1 K−1). However, the PCM’s latent heat of fusion is critical. Developers of PCMs for battery-powered flight must focus on enhanced latent heat of fusion, regardless of the adverse effect on thermal conductivity. In long-haul flight, an elongated cruise phase and higher altitude exasperate this problem. The unique characteristics of PCM offer a passive low-mass solution that merits further investigation for flight applications. Full article
(This article belongs to the Special Issue Smart Lithium-Ion Battery Systems: Advanced Modeling, State Estimation, and Control)
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<p>Simplified profiles of power demand and ambient temperature for typical regional passenger flights.</p> Full article ">Figure 2
<p>PCM temperature as a function of thermal energy stored in a PCM.</p> Full article ">Figure 3
<p>Typical Thevenin-based ECM of a cell [<a href="#B28-wevj-14-00015" class="html-bibr">28</a>].</p> Full article ">Figure 4
<p>(<b>a</b>) 2D cross-sectional view of the modeled battery pack and (<b>b</b>) boundary conditions of the modeled part of the battery pack.</p> Full article ">Figure 5
<p>Sensitivity test of R-value.</p> Full article ">Figure 6
<p>Profiles of (<b>a</b>) normalised power, (<b>b</b>) current, (<b>c</b>) voltage, and (<b>d</b>) ambient temperature over a flight by a regional passenger airplane.</p> Full article ">Figure 6 Cont.
<p>Profiles of (<b>a</b>) normalised power, (<b>b</b>) current, (<b>c</b>) voltage, and (<b>d</b>) ambient temperature over a flight by a regional passenger airplane.</p> Full article ">Figure 7
<p>Mesh independence test.</p> Full article ">Figure 8
<p>Simulation results of the three benchmark cases.</p> Full article ">Figure 9
<p>(<b>a</b>) Contour plot of normalised performance of BTMS against latent heat of fusion and thermal conductivity of PCM; (<b>b</b>) surface plot of normalised performance against latent heat of fusion and thermal conductivity of PCM; (<b>c</b>) graph of normalised performance against latent heat of fusion.</p> Full article ">Figure 9 Cont.
<p>(<b>a</b>) Contour plot of normalised performance of BTMS against latent heat of fusion and thermal conductivity of PCM; (<b>b</b>) surface plot of normalised performance against latent heat of fusion and thermal conductivity of PCM; (<b>c</b>) graph of normalised performance against latent heat of fusion.</p> Full article ">Figure 10
<p>Profiles of the average lithium-ion cell temperature throughout the progress of each modeled flight, where the initial temperature of the entire modeled domain (i.e., the battery pack including PCM and lithium-ion cells) is either 288.15 K or 298.15 K; (<b>a</b>) considers the case where the PCM melting temperature is 288.15 K, while (<b>b</b>) considers a melting temperature of 298.15 K and (<b>c</b>) considers a melting temperature of 308.15 K. The upper and lower limits refer to the optimal thermal conditions for the lithium-ion cells.</p> Full article ">Figure 11
<p>Profiles of the solid fraction of the PCM throughout the progress of each modeled flight, where the initial temperature of the entire modeled domain (i.e., battery pack including PCM and lithium-ion cells) is either 288.15 K or 298.15 K; (<b>a</b>) considers the case where the PCM melting temperature is 288.15 K, while (<b>b</b>) considers a melting temperature of 298.15 K and (<b>c</b>) considers a melting temperature of 308.15 K.</p> Full article ">
12 pages, 1878 KiB  
Article
State of Health Estimation Method for Lithium-Ion Batteries via Generalized Additivity Model and Transfer Component Analysis
by Mingqiang Lin, Chenhao Yan and Xianping Zeng
World Electr. Veh. J. 2023, 14(1), 14; https://doi.org/10.3390/wevj14010014 - 5 Jan 2023
Cited by 3 | Viewed by 3066
Abstract
Battery state of health (SOH) is a momentous indicator for aging severity recognition of lithium-ion batteries and is also an indispensable parameter of the battery management system. In this paper, an innovative SOH estimation algorithm based on feature transfer is proposed for lithium-ion [...] Read more.
Battery state of health (SOH) is a momentous indicator for aging severity recognition of lithium-ion batteries and is also an indispensable parameter of the battery management system. In this paper, an innovative SOH estimation algorithm based on feature transfer is proposed for lithium-ion batteries. Firstly, sequence features with battery aging information are sufficiently extracted based on the capacity increment curve. Secondly, transfer component analysis is employed to obtain the mapping that minimizes the data distribution difference between the training set and the test set in the shared feature space. Finally, the generalized additive model is investigated to estimate the battery health status. The experimental results demonstrate that the proposed algorithm is capable of forecasting the SOH for lithium-ion batteries, and the results are more outstanding than those of several comparison algorithms. The predictive error evaluation indicators for each battery are both less than 2.5%. In addition, satisfactory SOH estimation results can also be obtained by only relying on a small amount of data as the training set. The comparative experiments using traditional features and different machine learning methods also testify to the superiority of the proposed algorithm. Full article
(This article belongs to the Special Issue Recent Advances in Lithium-Ion Battery Safety and Aging Issues for Electric Vehicles)
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<p>The capacity degradation curves of eight cells in the Oxford dataset.</p> Full article ">Figure 2
<p>The incremental capacity curves of cell 1 in the Oxford dataset.</p> Full article ">Figure 3
<p>The flowchart of TCA-based SOH estimation algorithm.</p> Full article ">Figure 4
<p>SOH estimation results before and after feature transfer on the Oxford battery dataset: (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>,<b>m</b>) are the SOH prediction curves of cell 1 to cell 7; (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>l</b>,<b>n</b>) are the predicted error curves of cell 1 to cell 7.</p> Full article ">Figure 5
<p>SOH estimation results of different models on the Oxford battery dataset: (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>,<b>m</b>) are the SOH prediction curves of cell 1 to cell 7; (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>l</b>,<b>n</b>) are the predicted error curves of cell 1 to cell 7.</p> Full article ">
15 pages, 3610 KiB  
Article
Design and Application of the unIT-e2 Project Use Case Methodology
by Adrian Ostermann, Patrick Vollmuth and Valerie Ziemsky
World Electr. Veh. J. 2023, 14(1), 13; https://doi.org/10.3390/wevj14010013 - 5 Jan 2023
Cited by 2 | Viewed by 2542
Abstract
The ramp-up of electromobility requires cross-industry holistic solutions. However, bringing together stakeholders from different branches holds challenges. One prerequisite for successful collaboration is a uniform understanding of roles, processes, and interfaces. Based on existing methods and experience from former projects, this paper describes [...] Read more.
The ramp-up of electromobility requires cross-industry holistic solutions. However, bringing together stakeholders from different branches holds challenges. One prerequisite for successful collaboration is a uniform understanding of roles, processes, and interfaces. Based on existing methods and experience from former projects, this paper describes a method for the systematic description of use cases for smart charging of electric vehicles. This method enables a uniform understanding of all actors involved and guarantees application-oriented usability. The unIT-e2 use case methodology consists of the business-use case level and the technical-use case level, which describe the use case in a structured layout. The method was applied in all so-called clusters of project unIT-e2. In total, we identify 25 higher-level business use cases and highlight similarities and differences between them. Further, this paper describes the business-use case regulatory-defined grid-serving flexibility in detail. Full article
(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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<p>unIT-e<sup>2</sup> use-case methodology.</p> Full article ">Figure 1 Cont.
<p>unIT-e<sup>2</sup> use-case methodology.</p> Full article ">Figure 2
<p>Overview of BUCs in unIT-e<sup>2</sup> project grouped per cluster and incentive signal.</p> Full article ">Figure 3
<p>BUC regulatory-defined grid-serving unidirectional flexibility for privately owned home: description template (<b>top</b>) and e3-value model (<b>bottom</b>).</p> Full article ">Figure 3 Cont.
<p>BUC regulatory-defined grid-serving unidirectional flexibility for privately owned home: description template (<b>top</b>) and e3-value model (<b>bottom</b>).</p> Full article ">Figure 4
<p>TUC regulatory-defined grid-serving unidirectional flexibility for privately owned home: description template (<b>top</b>) and e3-value model (<b>bottom</b>).</p> Full article ">
12 pages, 3850 KiB  
Article
Optimal Design of Fractional-Order Electrical Network for Vehicle Mechatronic ISD Suspension Using the Structure-Immittance Approach
by Jie Hua, Yujie Shen, Xiaofeng Yang, Ying Zhang and Yanling Liu
World Electr. Veh. J. 2023, 14(1), 12; https://doi.org/10.3390/wevj14010012 - 4 Jan 2023
Cited by 2 | Viewed by 1972
Abstract
In order to more effectively design the structure of vehicle ISD (Inerter Spring Damper) suspension system using the inerter, this paper proposed a design method using a fractional-order electrical network structure of a mechatronic inerter for fractional-order electrical network components, according to the [...] Read more.
In order to more effectively design the structure of vehicle ISD (Inerter Spring Damper) suspension system using the inerter, this paper proposed a design method using a fractional-order electrical network structure of a mechatronic inerter for fractional-order electrical network components, according to the characteristics that the external electrical network of a mechatronic inerter can simulate the corresponding mechanical network structure equivalently. First, the 1/4 dynamic model of the suspension is constructed. The improved Oustaloup filtering algorithm is used to simulate fractional calculus, and the fractional order components are simulated. Then, the simulation model of the vehicle mechatronic ISD suspension is established. In order to simplify the electrical network, one resistance, one fractional inductance and one fractional capacitance are limited in the design of the fractional electrical network at the outer end of the mechatronic inerter. The structure-immittance approach is used to obtain two general layouts of all possible structures of three elements. At the same time, the optimal fractional electrical network structure and parameters are obtained by combining the optimization algorithm. The simulation results verify the performance of the fractional ISD suspension with the optimized structure, which can provide a new idea for the structural design of a fractional-order electrical network applied in vehicle mechatronic ISD suspension. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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<p>The schematic of ball-screw mechatronic inerter.</p> Full article ">Figure 2
<p>A quarter vehicle suspension model.</p> Full article ">Figure 3
<p>General structure of <span class="html-italic">Y</span><sub>1</sub>(s).</p> Full article ">Figure 4
<p>General structure of <span class="html-italic">Y</span><sub>2</sub>(s).</p> Full article ">Figure 5
<p>Pattern search optimization algorithm.</p> Full article ">Figure 6
<p>The optimized fractional-order electrical network structure.</p> Full article ">Figure 7
<p>Bode diagram comparison of two suspension systems.</p> Full article ">Figure 8
<p>Comparison of the vehicle body acceleration.</p> Full article ">Figure 9
<p>Comparison of the suspension working space.</p> Full article ">Figure 10
<p>Comparison of the dynamic tire load.</p> Full article ">
15 pages, 2255 KiB  
Article
Adaptive Robust Path Tracking Control for Autonomous Vehicles Considering Multi-Dimensional System Uncertainty
by Mengyuan Chen, Yue Ren and Minghui Ou
World Electr. Veh. J. 2023, 14(1), 11; https://doi.org/10.3390/wevj14010011 - 2 Jan 2023
Cited by 10 | Viewed by 2382
Abstract
As the bottom layer of the autonomous vehicle, path tracking control is a crucial element that provides accurate control command to the X-by-wire chassis and guarantees the vehicle safety. To overcome the deterioration of control performance for autonomous vehicle path-tracking controllers caused by [...] Read more.
As the bottom layer of the autonomous vehicle, path tracking control is a crucial element that provides accurate control command to the X-by-wire chassis and guarantees the vehicle safety. To overcome the deterioration of control performance for autonomous vehicle path-tracking controllers caused by modeling errors and parameter perturbation, an adaptive robust control framework is proposed in this paper. Firstly, the 2-DOF vehicle dynamic model is established and the non-singular fast terminal sliding mode control algorithm is adopted to formulate the control law. The unmeasured model disturbance and parameter perturbation is regarded as the system uncertainty. To enhance the control accuracy, the radial basis forward neural network is introduced to estimate such uncertainty in real time. Then, the dynamic model of an active front steering system is established. The model reference control algorithm is applied for the steering torque control considering model uncertainty brought by the dissipation of manufacturing and mechanical wear. Finally, the Simulink–CarSim co-simulation platform is used and the proposed control framework is validated in two test scenarios. The simulation results demonstrate the proposed adaptive robust control algorithm has satisfactory control performance and good robustness against the system uncertainty. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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<p>Control framework for vehicle path tracking.</p> Full article ">Figure 2
<p>The 2-DOP bicycle-tracking model.</p> Full article ">Figure 3
<p>The structure of RBFNN-based NFTSM control algorithm.</p> Full article ">Figure 4
<p>Active front wheel steering system.</p> Full article ">Figure 5
<p>The simulation results for scenario 1: (<b>a</b>) Global vehicle trajectory; (<b>b</b>)Steering wheel angle; (<b>c</b>) Lateral position error; (<b>d</b>) Orientation error.</p> Full article ">Figure 5 Cont.
<p>The simulation results for scenario 1: (<b>a</b>) Global vehicle trajectory; (<b>b</b>)Steering wheel angle; (<b>c</b>) Lateral position error; (<b>d</b>) Orientation error.</p> Full article ">Figure 6
<p>The comparison for three controllers: (<b>a</b>) Global vehicle trajectory with healthy system; (<b>b</b>) Lateral position error with healthy system; (<b>c</b>) Global vehicle trajectory with parameter perturbation; (<b>d</b>) Lateral position error with parameter perturbation.</p> Full article ">Figure 7
<p>The simulation results for scenario 2: (<b>a</b>) Global vehicle trajectory; (<b>b</b>) Steering wheel angle; (<b>c</b>) Lateral position error; (<b>d</b>) Orientation error.</p> Full article ">
3 pages, 1131 KiB  
Editorial
The Road to Green Mobility in Hong Kong
by Tiande Mo, Fengxiang Chen, Yu Li and Yang Luo
World Electr. Veh. J. 2023, 14(1), 10; https://doi.org/10.3390/wevj14010010 - 1 Jan 2023
Cited by 2 | Viewed by 2090
Abstract
Green mobility is in high demand in the 21st century [...] Full article
(This article belongs to the Special Issue Trends and Emerging Technologies in Electric Vehicles)
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<p>(<b>a</b>) Hong Kong’s first hydrogen-powered forklift launched by HKPC. (<b>b</b>) The fuel cell hybrid system inside.</p> Full article ">
20 pages, 3673 KiB  
Article
Integrated DC/DC Converter Topology Study for Fuel Cell Hybrid Vehicles with Two Energy Sources
by Weijin Xie, Wenguang Luo and Yongxin Qin
World Electr. Veh. J. 2023, 14(1), 9; https://doi.org/10.3390/wevj14010009 - 29 Dec 2022
Cited by 5 | Viewed by 2911
Abstract
Conventional hybrid vehicles with two energy sources require two separate on-board DC/DC converters to connect the battery and the fuel cell, which have the disadvantages of large size, high cost, high losses and few applicable operating conditions. To address this situation, this paper [...] Read more.
Conventional hybrid vehicles with two energy sources require two separate on-board DC/DC converters to connect the battery and the fuel cell, which have the disadvantages of large size, high cost, high losses and few applicable operating conditions. To address this situation, this paper proposes an optimized on-board integrated DC/DC converter with a non-isolated multi-port scheme that integrates a unidirectional port for the fuel cell and a bidirectional port for the battery and load. This can achieve a combined energy supply and recovery with a single integrated converter, effectively overcoming the above disadvantages. The optimized converter topology is relatively simple, and the magnetic losses of the transformer are removed. Furthermore, the switched capacitor is introduced as a voltage doubling unit to achieve high-gain output, so the fuel cell and battery voltage demand levels are reduced under the same load conditions. In addition, it has superior performance in system energy management for hybrid vehicles, which can distribute power and switch operating states by controlling the on/off of switching devices to make it suitable for five driving conditions. This paper discusses in detail the operating principles of the converter and analyzes its steady-state performance under five operating modes, derives its dynamic model, and proposes a proportional-integral control scheme. Finally, the simulation model of the topology is built by Matlab/Simulink software to verify the converter operation in each driving state, and the simulation experimental results verify the applicability of the proposed integrated DC/DC converter topology. Full article
(This article belongs to the Special Issue Power Electronics for Electric Vehicles)
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<p>The Structure of Integrated Converter for Fuel Cell Hybrid Vehicle.</p> Full article ">Figure 2
<p>Equivalent circuits of five different operating states: (<b>a</b>) State 1; (<b>b</b>) State 2; (<b>c</b>) State 3; (<b>d</b>) State 4; (<b>e</b>) State 5.</p> Full article ">Figure 3
<p>The equivalent circuit for capacitor charging and discharging: (<b>a</b>) charging circuit; (<b>b</b>) discharging circuit.</p> Full article ">Figure 4
<p>System control block diagram: (<b>a</b>) control block diagram of state 1 to 4 (<span class="html-italic">d</span><sub>1</sub> = <span class="html-italic">d</span><sub>2</sub> at state 1 and 2, <span class="html-italic">d</span><sub>1</sub> ≠ <span class="html-italic">d</span><sub>2</sub> at state 3 and 4); (<b>b</b>) control block diagram of state 5.</p> Full article ">Figure 5
<p>The effect of controller under working state 1 and 2: (<b>a</b>) output voltage under load switching conditions; (<b>b</b>) output voltage following the desired value schematic.</p> Full article ">Figure 6
<p>The effect of controller under working state 3: (<b>a</b>) output voltage under variable voltage scaling conditions; (<b>b</b>) result of proportional change in power input.</p> Full article ">Figure 7
<p>Output results for variable input voltage at operating state 5.</p> Full article ">Figure 8
<p>The simulation results of state 1 and 2: (<b>a</b>) the voltages of output and capacitor in state 1; (<b>b</b>) the average currents and their waveforms of inductors <span class="html-italic">L</span><sub>1</sub> and <span class="html-italic">L</span><sub>2</sub> in state 1; (<b>c</b>) the voltages of output and capacitor in state 2; (<b>d</b>) the average currents and their waveforms of inductors <span class="html-italic">L</span><sub>1</sub> and <span class="html-italic">L</span><sub>2</sub> in state 2.</p> Full article ">Figure 8 Cont.
<p>The simulation results of state 1 and 2: (<b>a</b>) the voltages of output and capacitor in state 1; (<b>b</b>) the average currents and their waveforms of inductors <span class="html-italic">L</span><sub>1</sub> and <span class="html-italic">L</span><sub>2</sub> in state 1; (<b>c</b>) the voltages of output and capacitor in state 2; (<b>d</b>) the average currents and their waveforms of inductors <span class="html-italic">L</span><sub>1</sub> and <span class="html-italic">L</span><sub>2</sub> in state 2.</p> Full article ">Figure 9
<p>The simulation results of state 3: (<b>a</b>) the voltages of output and capacitor in state 3; (<b>b</b>) the average currents and their waveforms of inductors <span class="html-italic">L</span><sub>1</sub> and <span class="html-italic">L</span><sub>2</sub> in state 3.</p> Full article ">Figure 10
<p>The simulation results of charging work: (<b>a</b>) the load and battery output voltage in state 4; (<b>b</b>) the average currents and waveforms in state 4.</p> Full article ">Figure 11
<p>The simulation results of the operation of the load braking energy feedback: (<b>a</b>) the battery charging voltage in state 5; (<b>b</b>) the inductance current in state 5.</p> Full article ">Figure 12
<p>Capacitor charging spike current waveform: (<b>a</b>) current without thermistor in series; (<b>b</b>) current with thermistor in series.</p> Full article ">Figure 13
<p>The output during state switching and its sequence: (<b>a</b>) voltage waveform of operating state switching; (<b>b</b>) current waveform of operating state switching; (<b>c</b>) switching sequence of operating states.</p> Full article ">Figure 14
<p>Charging voltage of battery port.</p> Full article ">Figure 15
<p>Charging voltage of battery port in feedback state.</p> Full article ">Figure 16
<p>Output efficiency in each state.</p> Full article ">
18 pages, 7951 KiB  
Article
State of Charge Estimation for Power Battery Base on Improved Particle Filter
by Xingtao Liu, Xiaojie Fan, Li Wang and Ji Wu
World Electr. Veh. J. 2023, 14(1), 8; https://doi.org/10.3390/wevj14010008 - 28 Dec 2022
Cited by 9 | Viewed by 2633
Abstract
In this paper, an improved particle filter (Improved Particle Swarm Optimized Particle Filter, IPSO-PF) algorithm is proposed to estimate the state of charge (SOC) of lithium-ion batteries. It solves the problem of inaccurate posterior estimation due to particle degradation. The algorithm divides the [...] Read more.
In this paper, an improved particle filter (Improved Particle Swarm Optimized Particle Filter, IPSO-PF) algorithm is proposed to estimate the state of charge (SOC) of lithium-ion batteries. It solves the problem of inaccurate posterior estimation due to particle degradation. The algorithm divides the particle population into three parts and designs different updating methods to realize self-variation and mutual learning of particles, which effectively promotes global development and avoids falling into local optimum. Firstly, a second-order RC equivalent circuit model is established. Secondly, the model parameters are identified by the particle swarm optimization algorithm. Finally, the proposed algorithm is verified under four different driving conditions. The results show that the root mean square error (RMSE) of the proposed algorithm is within 0.4% under different driving conditions, and the maximum error (ME) is less than 1%, showing good generalization. Compared with the EKF, PF, and PSO-PF algorithms, the IPSO-PF algorithm significantly improves the estimation accuracy of SOC, which verifies the superiority of the proposed algorithm. Full article
(This article belongs to the Special Issue Theory, Method and Application of New Energy and Intelligent Transportation)
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<p>Second-Order RC Equivalent Circuit Model.</p> Full article ">Figure 2
<p>Current of Incremental Current Condition.</p> Full article ">Figure 3
<p>Voltage of Incremental Current Condition.</p> Full article ">Figure 4
<p>Population Division.</p> Full article ">Figure 5
<p>Flow Chart of the SOC Estimation.</p> Full article ">Figure 6
<p>Current of DST Driving Condition.</p> Full article ">Figure 7
<p>Current of FUDS Driving Condition.</p> Full article ">Figure 8
<p>Current of US06 Driving Condition.</p> Full article ">Figure 9
<p>Current of BJDST Driving Condition.</p> Full article ">Figure 10
<p>Fitness Curve.</p> Full article ">Figure 11
<p>Errors of Terminal Voltage under DST Driving Condition.</p> Full article ">Figure 12
<p>Errors of Terminal Voltage under FUDS Driving Condition.</p> Full article ">Figure 13
<p>Errors of Terminal Voltage under US06 Driving Condition.</p> Full article ">Figure 14
<p>Errors of Terminal Voltage under BJDST Driving Condition.</p> Full article ">Figure 15
<p>Weight Distribution at SOC = 0.5.</p> Full article ">Figure 16
<p>Weight Distribution at SOC = 0.2.</p> Full article ">Figure 17
<p>SOC Estimation Results and Errors of DST Driving Condition.</p> Full article ">Figure 18
<p>SOC Estimation Results and Errors of Different Driving Conditions.</p> Full article ">
17 pages, 7484 KiB  
Article
Comparison of Interleaved Boost Converter and Two-Phase Boost Converter Characteristics for Three-Level Inverters
by Eiichi Sakasegawa, Rin Chishiki, Rintarou Sedutsu, Takumi Soeda, Hitoshi Haga and Ralph Mario Kennel
World Electr. Veh. J. 2023, 14(1), 7; https://doi.org/10.3390/wevj14010007 - 28 Dec 2022
Cited by 5 | Viewed by 3325
Abstract
A boost converter is used in various applications to obtain a higher voltage than the input voltage. One of the current main circuit systems for hybrid electric vehicles (HEVs) is a combination of a two-phase boost converter (parallel circuit) and a three-phase two-level [...] Read more.
A boost converter is used in various applications to obtain a higher voltage than the input voltage. One of the current main circuit systems for hybrid electric vehicles (HEVs) is a combination of a two-phase boost converter (parallel circuit) and a three-phase two-level inverter. In this study, we focus on the boost converter to achieve even higher efficiency and propose an interleaving scheme for a boost converter suitable for a three-level inverter (series circuit). The series circuit has two capacitors connected in series and makes it suitable as a power supply for a three-level inverter. We analyze the input current ripple of the series and parallel circuit in order to show the superiority of the series circuit. Furthermore, we propose a novel output voltage control strategy using an optimal regulator, namely a Linear Quadratic Regulator (LQR), for the series circuit. As a result, we found the input current ripple of the series circuit is smaller than the parallel circuit and demonstrated the superiority of the series circuit. The simulation and experimental results show the effectiveness of the proposed interleaving scheme and optimal regulator. Full article
(This article belongs to the Special Issue Power Converters and Electric Motor Drives)
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<p>Parallel circuit.</p> Full article ">Figure 2
<p>Series circuit.</p> Full article ">Figure 3
<p>Carriers and switching modes of interleaving method. (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>≤</mo> <mn>0.5</mn> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>&gt;</mo> <mn>0.5</mn> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Switching modes of parallel circuit. (<b>a</b>) MODE1; (<b>b</b>) MODE2; (<b>c</b>) MODE3; (<b>d</b>) MODE4.</p> Full article ">Figure 5
<p>Switching modes of series circuit. (<b>a</b>) MODE1; (<b>b</b>) MODE2; (<b>c</b>) MODE3; (<b>d</b>) MODE4.</p> Full article ">Figure 6
<p>Configuration of parallel circuit with PI controller.</p> Full article ">Figure 7
<p>Configuration of series circuit with PI controller.</p> Full article ">Figure 8
<p>Configuration of series circuit with LQR.</p> Full article ">Figure 9
<p>Experimental setup.</p> Full article ">Figure 10
<p>Simulated results for weight coefficients design. (<b>a</b>) Q = diag([1,1,1,1,1]); (<b>b</b>) Q = diag([1,1,1,100,100]); (<b>c</b>) Q = diag([5,5,5,100,100]); (<b>d</b>) Q = diag([5,5,5,100,1000]); (<b>e</b>) Q = diag([5,5,2,100,1000]); (<b>f</b>) Q = diag([5,5,10,100,1000]).</p> Full article ">Figure 11
<p>Steady state characteristics of series circuit.</p> Full article ">Figure 12
<p>Experimental results of input current ripple characteristics of parallel circuit. (<b>a</b>) <span class="html-italic">D</span> = 0.3; (<b>b</b>) <span class="html-italic">D</span> = 0.5; (<b>c</b>) <span class="html-italic">D</span> = 0.6.</p> Full article ">Figure 13
<p>Experimental results of input current ripple characteristics of series circuit. (<b>a</b>) <span class="html-italic">D</span> = 0.3; (<b>b</b>) <span class="html-italic">D</span> = 0.5; (<b>c</b>) <span class="html-italic">D</span> = 0.6.</p> Full article ">Figure 14
<p>Simulated results of input current ripple characteristics of parallel circuit. (<b>a</b>) <span class="html-italic">D</span>=0.3; (<b>b</b>) <span class="html-italic">D</span> = 0.5; (<b>c</b>) <span class="html-italic">D</span> = 0.6.</p> Full article ">Figure 15
<p>Simulated results of input current ripple characteristics of series circuit. (<b>a</b>) <span class="html-italic">D</span> = 0.3; (<b>b</b>) <span class="html-italic">D</span> = 0.5; (<b>c</b>) <span class="html-italic">D</span> = 0.6.</p> Full article ">Figure 16
<p>Input current ripple characteristics for duty ratio.</p> Full article ">Figure 17
<p>Step response (150 V to 200 V). (<b>a</b>) PI control; (<b>b</b>) LQR.</p> Full article ">Figure 18
<p>Load variation (200 W to 500 W). (<b>a</b>) PI control; (<b>b</b>) LQR.</p> Full article ">Figure 19
<p>Load variation (500 W to 200 W). (<b>a</b>) PI control; (<b>b</b>) LQR.</p> Full article ">Figure 20
<p>Efficiency characteristics for output voltage.</p> Full article ">Figure 21
<p>Efficiency characteristics for output power.</p> Full article ">Figure 22
<p>Loss comparison of parallel circuit when output voltage is 280 V.</p> Full article ">Figure 23
<p>Loss comparison of series circuit when output voltage is 280 V.</p> Full article ">
20 pages, 3829 KiB  
Article
Thermal Management System of the UNICARagil Vehicles—A Comprehensive Overview
by Daniel Gehringer, Timo Kuthada and Andreas Wagner
World Electr. Veh. J. 2023, 14(1), 6; https://doi.org/10.3390/wevj14010006 - 28 Dec 2022
Cited by 6 | Viewed by 3397
Abstract
The collaboration project UNICARagil aiming to develop new autonomous battery electric vehicle concepts has progressed and the four vehicle prototypes have been built up. All seven universities and six industrial partners have worked towards this milestone. At the time of writing the four [...] Read more.
The collaboration project UNICARagil aiming to develop new autonomous battery electric vehicle concepts has progressed and the four vehicle prototypes have been built up. All seven universities and six industrial partners have worked towards this milestone. At the time of writing the four vehicles are operational and can be driven by a safety driver using a sidestick. The automated driving functions are being applied on the test track and first demonstrations are carried out. This paper gives an overview of the results, which have been achieved within the work package of the thermal onboard network. The thermal management system including the heating, ventilation and air conditioning system and its development process is explained in detail. Furthermore, climate chamber measurements with prototype hardware of a sensor data processing computer and the integration of the air conditioning control unit into the vehicle’s automotive service-oriented architecture framework are described. A coupled simulation approach to predict occupant thermal comfort in one vehicle variant is presented. Simulation results using environmental conditions typical for a European summer show a comfortable environment for all six occupants. In addition, the simulation and development process of a thermoelectric heat pump is shown. First measurement results with the heat pump on a test bench are highlighted which show an achievable coefficient of performance greater than two. Full article
(This article belongs to the Special Issue Advances in Electrification and Thermal Management of Propulsion Systems)
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Figure 1
<p>Implemented thermal management system topology in UNICARagil.</p> Full article ">Figure 2
<p>(<b>a</b>) Isometric view of the large vehicle variant (autoSHUTTLE); (<b>b</b>) vehicle package with HVAC and cooling components highlighted.</p> Full article ">Figure 3
<p>Thermal testing of the DPU at 50 °C test chamber temperature: (<b>a</b>) with case fans; (<b>b</b>) without case fans.</p> Full article ">Figure 4
<p>Input-output model of the HVAC-System ECU.</p> Full article ">Figure 5
<p>Target interior temperature curves used by the controller, based on [<a href="#B21-wevj-14-00006" class="html-bibr">21</a>,<a href="#B22-wevj-14-00006" class="html-bibr">22</a>,<a href="#B23-wevj-14-00006" class="html-bibr">23</a>].</p> Full article ">Figure 6
<p>AutoSHUTTLE cabin simulation model: (<b>a</b>) isometric view of the model with six manikins with colored segments; (<b>b</b>) HVAC box with inlet and ducting.</p> Full article ">Figure 7
<p>Simulated thermal sensation and comfort results of all occupants in the summer case.</p> Full article ">Figure 8
<p>(<b>a</b>) Thermoelectric leg pair; (<b>b</b>) Coefficient of performance versus supply current in dependence of temperature difference [<a href="#B35-wevj-14-00006" class="html-bibr">35</a>].</p> Full article ">Figure 9
<p>Final optimization of cooling plate versions: (<b>a</b>) convection flux in excerpts of the cooling plate channels; (<b>b</b>) Nusselt number over pressure coefficient. Based on [<a href="#B39-wevj-14-00006" class="html-bibr">39</a>].</p> Full article ">Figure 10
<p>Exploded view of the thermoelectric heat pump: (<b>a</b>) Cabin cooling plate with final coolant channel design; (<b>b</b>) Complete assembly with all three cooling plates and TEMs.</p> Full article ">Figure 11
<p>Measurement results showing coefficient of performance over-heating power: (<b>a</b>) with pre-conditioned coolant loop; (<b>b</b>) without pre-conditioned coolant loop. Measurement results taken from [<a href="#B43-wevj-14-00006" class="html-bibr">43</a>].</p> Full article ">
16 pages, 5212 KiB  
Article
Development of a Personnel Management and Position and Energy Tracking System for Electric Vehicles
by Olugbenga Kayode Ogidan, Celestine Aghaukwu, Oluwagbotemi Oluwapelumi, Success Jeremiah, Edesemi Adokeme and Omowunmi Mary Longe
World Electr. Veh. J. 2023, 14(1), 5; https://doi.org/10.3390/wevj14010005 - 25 Dec 2022
Cited by 2 | Viewed by 2327
Abstract
The challenges faced by managers of transportation systems in developing nations such as Nigeria are numerous. These include driver scheduling, which, in many cases, is still being done manually; diversion of vehicles to unauthorized routes by drivers for selfish reasons results in illegal [...] Read more.
The challenges faced by managers of transportation systems in developing nations such as Nigeria are numerous. These include driver scheduling, which, in many cases, is still being done manually; diversion of vehicles to unauthorized routes by drivers for selfish reasons results in illegal use of fuel meant for official duties, causing the organization lose considerable revenue. In its drive to reduce its carbon footprint, Elizade University, Nigeria, is embarking on the development and use of electric vehicles (EV) as a means of transportation within the university campus. This research is geared towards supporting this initiative by developing an EV tracking system that combines tracking of EV drivers with vehicle position and battery power (energy) tracking in order to mitigate the challenges outlined above. Personnel tracking was achieved using an RFID-enabled staff identity card that authenticates authorized drivers before activating the vehicle ignition system, position tracking was achieved using a geographical positioning system (GPS), and current and voltage sensors were used for tracking of electric vehicle power. Tests revealed that the EV system administrator operated through a personal computer was able to track the EV driver, position and power through a web interface/Google Maps and e-mail in real time. Whereas previous studies either considered tracking of vehicle position or power without personnel, others tracked personnel with less emphasis on the vehicle position or energy. In this study, we combined different technologies such as RFID, GPS and power sensors to consider EV administration in a holistic manner, thereby providing intervention in an infrastructurally deficient setting. Full article
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<p>Architecture of Electric (E) - mobility tracking system for an EV.</p> Full article ">Figure 2
<p>Block diagram of RFID-based personnel tracking.</p> Full article ">Figure 3
<p>RFID-based personnel administration circuit diagram.</p> Full article ">Figure 4
<p>Block diagram of the GPS tracking system.</p> Full article ">Figure 5
<p>Flow chart illustrating GPS tracking operation of the EV.</p> Full article ">Figure 6
<p>Block diagram of the EV energy tracking system.</p> Full article ">Figure 7
<p>Circuit diagram of the EV energy tracking system.</p> Full article ">Figure 8
<p>Flow chart of the EV energy tracking operation.</p> Full article ">Figure 9
<p>System front view.</p> Full article ">Figure 10
<p>Personnel, position and energy tracking values in the database.</p> Full article ">Figure 11
<p>Dashboard of personnel, position and energy tracking on the web interface.</p> Full article ">Figure 12
<p>RFID card logs used for personnel management.</p> Full article ">Figure 13
<p>Vehicle position showing on Google Maps.</p> Full article ">Figure 14
<p>(<b>a</b>) GPS data on the LCD display; (<b>b</b>) GPS data sent to user by e-mail.</p> Full article ">Figure 15
<p>Energy tracking section on the web page.</p> Full article ">
21 pages, 7577 KiB  
Article
Design Optimization of a New Hybrid Excitation Drive Motor for New Energy Vehicles
by Shilong Yan, Xueyi Zhang, Zhidong Gao, Aichuan Wang, Yufeng Zhang, Mingjun Xu and Sizhan Hua
World Electr. Veh. J. 2023, 14(1), 4; https://doi.org/10.3390/wevj14010004 - 23 Dec 2022
Cited by 3 | Viewed by 2041
Abstract
In this paper, a new hybrid excitation drive motor (HEDM) was proposed to solve the problem of an uncontrollable magnetic field of a permanent magnet motor. The rotor part of the motor was composed of a combined magnetic pole permanent magnet rotor and [...] Read more.
In this paper, a new hybrid excitation drive motor (HEDM) was proposed to solve the problem of an uncontrollable magnetic field of a permanent magnet motor. The rotor part of the motor was composed of a combined magnetic pole permanent magnet rotor and a brushless electric claw rotor, in which the combined magnetic pole permanent magnet rotor has a parallel magnetic circuit structure. According to the characteristics of the parallel rotor structure, the equivalent magnetic circuit model was established, and the no-load leakage flux coefficient of the claw pole rotor was calculated. The Taguchi method was used for objective optimization of the permanent magnet rotor structure. The distortion rate of no-load back electromotive force (EMF) was taken as the first optimization goal; the cogging torque and the average torque were taken as the second optimization goal; and the torque fluctuation coefficient was a constraint condition. The optimal parameter matching under the mixed horizontal matrix was obtained. The parameters of the claw pole were optimized by using the method of uniform variables, and the dimension parameters of the motor were obtained. Finite element analysis and prototype tests were carried out for the optimized motor structure. The rationality and feasibility of the new HEDM as a vehicle motor were verified, which provided a possibility for the application of the new energy vehicle drive motor field. Full article
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<p>The structure of the hybrid excitation drive motor.</p> Full article ">Figure 2
<p>Comparison diagrams of flux paths. (<b>a</b>) Magnetic flux path of initial structure. (<b>b</b>) Magnetic flux path of improved structure.</p> Full article ">Figure 3
<p>Equivalent magnetic circuit model of combined pole permanent magnet rotor.</p> Full article ">Figure 4
<p>Magnetic circuit diagram of claw pole motor with brushless electric excitation. (<b>a</b>) Electric excitation main flux path with forward current. (<b>b</b>) Electric excitation flux path with forward current.</p> Full article ">Figure 5
<p>Equivalent magnetic circuit model of claw pole motor with brushless electric excitation.</p> Full article ">Figure 6
<p>Schematic diagram of optimization parameters of combined magnetic pole PM rotor. (<b>a</b>) Initial structure and (<b>b</b>) Improved structure.</p> Full article ">Figure 7
<p>Influence of optimization factor. (<b>a</b>) Cogging torque; (<b>b</b>) Output torque; and (<b>c</b>) Back-EMF distortion rate.</p> Full article ">Figure 8
<p>Variation of air-gap flux density with the thickness of claw pole under different excitation currents. (<b>a</b>) The thickness of claw heel; and (<b>b</b>) The thickness of claw tip.</p> Full article ">Figure 9
<p>Variation of air gap magnetic density with pole arc coefficient under different excitation currents. (<b>a</b>) Heel pole arc coefficient; and (<b>b</b>) tip pole arc coefficient.</p> Full article ">Figure 10
<p>Comparison diagram of rotor before and after optimization. (<b>a</b>) Rotor magnetic field line trend comparison before and after optimization. (<b>b</b>) Rotor magnetic flux density comparison before and after optimization.</p> Full article ">Figure 11
<p>Wave and harmonic of no-load back EMF before and after optimization. (<b>a</b>) Back-EMF wave. (<b>b</b>) Harmonic amplitude.</p> Full article ">Figure 12
<p>Cogging torque and output torque before and after optimization. (<b>a</b>) Cogging torque wave. (<b>b</b>) Output torque wave.</p> Full article ">Figure 13
<p>Diagram of claw pole motor. (<b>a</b>) Magnetic flux vector. (<b>b</b>) Flux density cloud.</p> Full article ">Figure 14
<p>Comparison of air-gap magnetic density waveforms of the claw pole motor before and after optimization.</p> Full article ">Figure 15
<p>The rotor structure of the HEDM. (<b>a</b>) Structure of combined magnetic pole PM rotor. (<b>b</b>) Structure of brushless electric excitation claw pole rotor.</p> Full article ">Figure 16
<p>The cogging torque test platform.</p> Full article ">Figure 17
<p>The cogging torque experimental curve.</p> Full article ">Figure 18
<p>Dynamometer test platform.</p> Full article ">Figure 19
<p>Magnetic modulation characteristic curve of prototype.</p> Full article ">Figure 20
<p>Output characteristics of the motor at different feature points.</p> Full article ">
24 pages, 6631 KiB  
Review
Research on the Application and Control Strategy of Energy Storage in Rail Transportation
by Dixi Xin, Jianlin Li and Chang’an Liu
World Electr. Veh. J. 2023, 14(1), 3; https://doi.org/10.3390/wevj14010003 - 23 Dec 2022
Cited by 4 | Viewed by 2369
Abstract
With the development of the global economy and the increase in environmental awareness, energy technology in transportation, especially the application of energy storage technology in rail transportation, has become a key area of research. Rail transportation systems are characterized by high energy consumption [...] Read more.
With the development of the global economy and the increase in environmental awareness, energy technology in transportation, especially the application of energy storage technology in rail transportation, has become a key area of research. Rail transportation systems are characterized by high energy consumption and poor power quality due to the more flexible regulation capability of energy storage technology in these aspects. This paper summarizes the latest research results on energy storage in rail transportation systems, matches the characteristics of energy storage technologies with the energy storage needs of rail transportation, and analyzes the operation of energy storage systems in different scenarios. The adaptability of batteries, supercapacitors, and flywheels as energy storage systems for rail transportation is summarized and compared. The topologies and integration methods of various energy storage systems are studied. The control strategies under each control of rail transportation are summarized and proposed. The future development direction of energy storage system for rail transportation prospects and the corresponding reference is provided for the engineering of energy storage technology in the field of rail transportation. Full article
(This article belongs to the Special Issue Theory, Method and Application of New Energy and Intelligent Transportation)
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Figure 1
<p>The typical DC traction power network with multi-trains.</p> Full article ">Figure 2
<p>The DC traction energy system topology.</p> Full article ">Figure 3
<p>The typical AC traction power network with multi-trains.</p> Full article ">Figure 4
<p>The AC traction energy system topology.</p> Full article ">Figure 5
<p>Structural diagram of the two-stage converter.</p> Full article ">Figure 6
<p>Topology of half-bridge bidirectional DC/DC converters.</p> Full article ">Figure 7
<p>Topology of BUCK-BOOST bidirectional DC/DC converter.</p> Full article ">Figure 8
<p>Topology of Cuk bidirectional DC/DC converter.</p> Full article ">Figure 9
<p>Topology of Sepic/zeta bidirectional DC/DC converter.</p> Full article ">Figure 10
<p>Topology of isolated full-bridge bidirectional DC/DC converter.</p> Full article ">Figure 11
<p>Topology of isolated half-bridge bi-directional DC/DC converter.</p> Full article ">Figure 12
<p>Topology of isolated push–pull bidirectional DC/DC converter.</p> Full article ">Figure 13
<p>Structural diagram of single converter integrated systems.</p> Full article ">Figure 14
<p>Structural diagram of multi-converter converter integrated systems.</p> Full article ">Figure 15
<p>Schematic diagram of a parallel system of supercapacitors and loads.</p> Full article ">Figure 16
<p>Schematic diagram of a two-stage converter system with supercapacitor and load.</p> Full article ">Figure 17
<p>Schematic diagram of a modified supercapacitor and load two-stage converter system.</p> Full article ">Figure 18
<p>Schematic diagram of the additional supercapacitor structure.</p> Full article ">Figure 19
<p>Schematic diagram of the plug-in converter with supercapacitor.</p> Full article ">Figure 20
<p>The plug-in converter topology with supercapacitor.</p> Full article ">Figure 21
<p>The Quasi-Z source converter topology with supercapacitor.</p> Full article ">Figure 22
<p>Direct AC converters with flywheel.</p> Full article ">Figure 23
<p>Indirect AC converters with flywheel.</p> Full article ">Figure 24
<p>Indirect AC converters with the boost converter.</p> Full article ">Figure 25
<p>Topology of full-bridge inverter with flywheel.</p> Full article ">Figure 26
<p>Topology of multilevel inverter with flywheel.</p> Full article ">Figure 27
<p>Topology of matrix converter with flywheel.</p> Full article ">Figure 28
<p>Schematic diagram of the DC bus integration system with flywheel.</p> Full article ">Figure 29
<p>Schematic diagram of the AC bus integration system with flywheel.</p> Full article ">Figure 30
<p>Power compensation vector diagram.</p> Full article ">Figure 31
<p>Block diagram of integrated power quality compensation logic.</p> Full article ">Figure 32
<p>Block diagram of DC outer loop control.</p> Full article ">Figure 33
<p>Block diagram of AC inner loop control.</p> Full article ">Figure 34
<p>Voltage-based control curves for energy storage.</p> Full article ">Figure 35
<p>Block diagram of fuzzy control of energy storage.</p> Full article ">Figure 36
<p>Block diagram of energy storage system model prediction.</p> Full article ">
14 pages, 5051 KiB  
Article
Current Control Method of Vehicle Permanent Magnet Synchronous Motor Based on Active Disturbance Rejection Control
by Jinyu Wang, Qiang Miao, Xiaomin Zhou, Lipeng Sun, Dawei Gao and Haifeng Lu
World Electr. Veh. J. 2023, 14(1), 2; https://doi.org/10.3390/wevj14010002 - 23 Dec 2022
Cited by 4 | Viewed by 2603
Abstract
Due to the frequently changing working conditions and complex operating environment of electric vehicle permanent magnet synchronous motor(PMSM), the motor parameters change dramatically. However, the performance of the PI current regulator, which is the most widely used, is sensitive to motor parameters and [...] Read more.
Due to the frequently changing working conditions and complex operating environment of electric vehicle permanent magnet synchronous motor(PMSM), the motor parameters change dramatically. However, the performance of the PI current regulator, which is the most widely used, is sensitive to motor parameters and has weak robustness, which will lead to the deterioration of motor control system performance. To address this problem, active disturbance rejection control (ADRC) technology is applied to the PMSM current loop control. Firstly, the traditional ADRC current regulator is designed, and the performance and parameter tuning laws of the extended state observer are analyzed by the method of frequency domain analysis. Then, the traditional ADRC algorithm is improved in three aspects: observation error compensation, utilization of model information and anti-windup. After that, simulations and bench test validation are performed. The simulation results show that the improved ADRC current regulator is more robust in the face of parameter changes. The torque step test results show that the improved ADRC current regulator has fast dynamic response without overshoot and has high robustness when the motor parameters change. The dynamic test results show that the improved ADRC current regulator has high robustness when the load, speed and motor parameters change, and the anti-windup measures designed can effectively overcome the integral saturation phenomenon. Full article
(This article belongs to the Special Issue Recent Advances in Electric Motor Drives for Electrified Mobility)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>ADRC current regulator.</p> Full article ">Figure 2
<p>Bode diagram of observation error transfer function: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mrow> <msub> <mi>e</mi> <mrow> <mi>d</mi> <mn>1</mn> <mo>/</mo> <mi>q</mi> <mn>1</mn> </mrow> </msub> </mrow> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mrow> <msub> <mi>e</mi> <mrow> <mi>d</mi> <mn>2</mn> <mo>/</mo> <mi>q</mi> <mn>2</mn> </mrow> </msub> </mrow> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p> Full article ">Figure 3
<p>PMSM single closed loop control block diagram.</p> Full article ">Figure 4
<p>Dq-axis current waveforms: (<b>a</b>) d-axis current; (<b>b</b>) q-axis current.</p> Full article ">Figure 5
<p>Dq-axis voltage waveforms: (<b>a</b>) d-axis voltage; (<b>b</b>) q-axis voltage.</p> Full article ">Figure 6
<p>Physical picture of test bench.</p> Full article ">Figure 7
<p>Peak torque step response(200 r·min<sup>−1</sup>): (<b>a</b>) d-axis current; (<b>b</b>) q-axis current.</p> Full article ">Figure 8
<p>Small torque step response(200 r·min<sup>−1</sup>): (<b>a</b>) d-axis current; (<b>b</b>) q-axis current.</p> Full article ">Figure 9
<p>PMSM external characteristic curve.</p> Full article ">Figure 10
<p>Voltage vector amplitude.</p> Full article ">Figure 11
<p>Dq-axis current waveforms: (<b>a</b>) d-axis current; (<b>b</b>) q-axis current.</p> Full article ">Figure 12
<p>Total disturbance observed value.</p> Full article ">Figure A1
<p>Dq-axis inductance contour map: (<b>a</b>) d-axis inductance; (<b>b</b>) q-axis inductance.</p> Full article ">
12 pages, 7557 KiB  
Article
A Discontinuous Modulation Method with Variable Clamping Interval Width of the Modular Multilevel Converter
by Xin Gu, Langang Ma, Guozheng Zhang and Xuefeng Jin
World Electr. Veh. J. 2023, 14(1), 1; https://doi.org/10.3390/wevj14010001 - 22 Dec 2022
Viewed by 1638
Abstract
The modular multilevel converter (MMC) has been widely used because of the advantages of easier expansion, lower harmonic distortion and higher output voltage level. If the MMC is adapted to high voltage application, more submodules need to be connected in series in each [...] Read more.
The modular multilevel converter (MMC) has been widely used because of the advantages of easier expansion, lower harmonic distortion and higher output voltage level. If the MMC is adapted to high voltage application, more submodules need to be connected in series in each arm. Thus, the switching loss needs to be considered a key issue. A discontinuous modulation method with variable clamping interval width is proposed in this paper in order to reduce the switching loss under variable power factor conditions. Different widths of the clamping interval can be selected according to the requirements of the system. Meanwhile, the capacitor voltage ripple of the submodules can also be reduced. The feasibility and effectiveness of the proposed modulation method are verified under a RT-LAB rapid control prototype based MMC system. Full article
(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)
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<p>Topology of the three-phase modular multilevel converter (MMC).</p> Full article ">Figure 2
<p>Four common clamp state area division.</p> Full article ">Figure 3
<p>Clamping factor λ Schematic diagram of clamping interval.</p> Full article ">Figure 4
<p>System control block diagram.</p> Full article ">Figure 5
<p>Sector division diagram.</p> Full article ">Figure 6
<p>Four clamping interval widths.</p> Full article ">Figure 7
<p>Example of discontinuous modulation strategy for variable load power factor.</p> Full article ">Figure 8
<p>MMC experimental system diagram.</p> Full article ">Figure 9
<p>Experimental waveforms of eight clamping widths under the condition of <span class="html-italic">m</span> = 0.9.</p> Full article ">Figure 10
<p>Experimental waveforms of eight clamping widths under the condition of <span class="html-italic">m</span> = 0.3.</p> Full article ">Figure 11
<p>Converter working efficiency.</p> Full article ">Figure 12
<p>Capacitor voltage ripple.</p> Full article ">Figure 13
<p>Output current THD.</p> Full article ">Figure 14
<p>Comparison of experimental waveform under the condition of 5 Ω and 10 mH.</p> Full article ">Figure 15
<p>Comparison of experimental waveform under the condition of 10 Ω and 30 mH.</p> Full article ">
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