CN114460914A - Hardware-in-loop test system and test method for new energy vehicle controller - Google Patents
Hardware-in-loop test system and test method for new energy vehicle controller Download PDFInfo
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Abstract
The invention discloses a hardware-in-loop test system and a test method for a new energy vehicle controller, which comprises the following steps: the system comprises an upper computer, a test cabinet and a whole vehicle controller; the upper computer is connected with the test cabinet through an Ethernet; the test cabinet is in communication connection with the vehicle control unit; the test cabinet comprises a real-time simulation system, the real-time simulation system is used for operating a test model, and the step A: acquiring hardware-in-loop test data of the vehicle controller, analyzing hardware-in-loop test requirements, and editing a test requirement matrix analysis list; and B, step B: according to the analysis of the hardware-in-loop test requirements, setting a hardware-in-loop test environment of the whole vehicle controller; and C: and generating an in-loop test estimation result of the hardware of the vehicle controller based on the test requirement matrix analysis list and the built test environment of the vehicle controller.
Description
Technical Field
The invention belongs to the field of hardware-in-loop test systems, and particularly relates to a hardware-in-loop test system and a hardware-in-loop test method for a new energy vehicle controller.
Background
The whole vehicle control system is a core control system of the new energy vehicle, and the safety, the dynamic property, the energy consumption economy and the driving smoothness of the new energy vehicle are closely related to the whole vehicle control system. The whole vehicle control system is used as a core control system of the new energy vehicle, and the hardware-in-loop test of the whole vehicle control system is especially important for the safety verification of the new energy vehicle. How to improve the hardware in-loop test quality of the finished automobile control system and improve the hardware in-loop test efficiency of the finished automobile control system is a most concerned problem for the research and development of the finished automobile control system and the managers.
Conventionally, for the hardware-in-loop test of the finished automobile control system, only hardware-in-loop test data collection, hardware-in-loop test requirement analysis, hardware-in-loop test execution and hardware-in-loop test summary are performed, and the hardware does not perform defect measurement before the loop test execution, so that the effective evaluation of the test sufficiency and the test quality after the loop test of the hardware is finished is not facilitated, and particularly, the newly developed finished automobile control system is targeted.
Disclosure of Invention
In order to improve the quality and efficiency of hardware-in-loop testing, the invention designs a hardware-in-loop testing method of a new energy vehicle control system based on defect estimation.
In order to solve the problems in the prior art, the invention adopts the technical scheme that:
a hardware-in-loop test system for a new energy vehicle control unit, the system comprising:
host computer, test cabinet and vehicle control unit.
The upper computer is connected with the test cabinet through the Ethernet.
The test cabinet is in communication connection with the vehicle control unit.
Further, the test cabinet includes a real-time simulation system, the real-time simulation system is used for operating a test model, and the test model includes: the whole vehicle power model comprises a vehicle dynamic model, a driving motor model and a battery model. The main parameters of the vehicle dynamic model comprise the servicing quality, the position of a mass center, the windward area, the radius of a tire, the main reduction ratio and the like; the main parameters of the driving motor model are motor rated/peak power efficiency characteristic data; the battery model mainly comprises charge-discharge characteristic data of monomers with different numbers of series-parallel connection and different temperatures; the driving environment model comprises wind speed, road rolling resistance coefficient, altitude and the like; the road spectrum model comprises various typical working condition data; the driver and cab models are divided into a driver model and a cab model. The driver model simulates the driving habits of different drivers according to the opening information of an accelerator pedal and a brake pedal of a real vehicle road test; the cab model simulates some cab panel signals, so that hardware-in-loop test input is facilitated; the limit condition model is mainly used for quickly and conveniently setting various abnormal fault information.
Furthermore, the upper computer is connected with the vehicle control unit through a calibration observation tool and used for reading a test operation result, the vehicle control unit is connected with the test cabinet through a wire harness, and signals transmitted by the wire harness mainly comprise various hard wire signals and CAN wire signals.
A hardware-in-loop testing method for a new energy vehicle controller comprises the following steps:
step A: acquiring hardware-in-loop test data of the vehicle controller, analyzing the hardware-in-loop test requirements, and editing a test requirement matrix analysis list.
The hardware-in-loop test data of the vehicle controller comprises a control system communication network topology, a vehicle controller communication matrix, a software and hardware interface specification and a vehicle controller function specification.
The step A comprises the following steps: and defining a hardware-in-loop test range, a hardware-in-loop test function item, a hardware-in-loop test depth and a hardware-in-loop test target of the whole vehicle controller in the requirement analysis matrix.
And B: and B, according to the analysis of the hardware-in-loop test requirements, building a hardware-in-loop test environment of the vehicle controller, and according to the limit working condition model built in the step A in the test depth.
The hardware-in-loop test environment comprises a vehicle model, a driving environment model, a road spectrum model, a driver and cab model, a battery model and a motor model.
Step B1: and (3) building a hardware-in-loop test environment of the vehicle control unit in modeling software of the upper computer, and compiling.
Step B2: and configuring a network mapping relation of nodes in VeriString test management software of the upper computer and a hard-line signal mapping relation of hardware of the vehicle control unit and the test cabinet according to the network topological structure of the vehicle control unit.
Step B3: and deploying the configured hardware-in-loop test environment of the vehicle control unit into a test cabinet in Veristand software, and simulating the in-loop test environment for running the vehicle control unit in real time by the test cabinet.
And C: and determining a hardware-in-loop test defect estimation algorithm and hardware-in-loop test result evaluation based on the test requirement matrix analysis list and the hardware-in-loop test environment, and generating hardware-in-loop test defect estimation.
Step D: and setting a test framework of the whole vehicle controller, a test case design method of each sub-function, the number of test cases of each sub-function, the priority of test execution and a test cut-off criterion based on hardware-in-loop test defect estimation.
Step E: performing hardware-in-loop test, specifically comprising the following steps:
and designing the test case according to the set test case design method.
And executing the test cases according to the set test execution priority, and recording the execution results of the test cases.
And stopping test execution according to the estimated test stopping criterion.
Step F: hardware was evaluated in the loop test.
And evaluating the hardware-in-loop test of the vehicle controller according to the test case execution result and the hardware-in-loop test result evaluation to obtain a hardware-in-loop test evaluation result.
Step G: and optimizing the hardware-in-loop test, and improving the defect evaluation of the hardware-in-loop test or the set test environment based on the evaluation result of the hardware-in-loop test.
Step H: and D, repeating the step D to the step F based on an improved hardware-in-loop test defect estimation algorithm until the test evaluation reaches the hardware-in-loop test target.
Further, the step C specifically includes a step C1: compiling a script file by utilizing Python software, identifying a test requirement matrix analysis list and a built test environment of the whole vehicle controller, determining a hardware-in-loop test defect estimation algorithm and a defect result measurement criterion, and calculating hardware-in-loop test defect estimation according to BugNUM;
the formula I is as follows:
BugNUM＝A×λA+(IN1+IN2+OUT)×λPort+MAX{NUM1，NUM2}×λNUM+Ff×λf
in the first formula:
a is the number of associated analog input signals.
λAAnd counting the contribution rate of the number of the analog input signals to the number of BUGs for the history.
IN1The number of other hard-wired input signals than the analog signal.
IN2The number of CAN input signals.
OUT is the number of output signals.
λPORTAnd testing the contribution rate of the historical statistical interface to the number of BUGs.
NUM1 is the number of relevant test items.
NUM2 is the number of components associated with the test item.
λNUMAnd testing the contribution rate of the historical statistical function correlation analysis to the number of BUGs.
Ff is the number of sub-function items of the test item.
And f, carrying out historical statistics on the contribution rate of the number of the sub-function items to the number of BUGs.
Step C2: and performing hardware-in-loop test defect estimation to generate hardware-in-loop test defect estimation.
Further, in the step E, the test case with the highest priority is executed, and if the test case meets the test cutoff criterion, the hardware-in-loop test execution result is evaluated.
Further, in the step F, computing a hardware-in-loop test result evaluation BugEval, and when an absolute value of the hardware-in-loop test result evaluation is not less than 27, analyzing the setting of the hardware in the loop test environment; when the hardware in-loop test result evaluation absolute value is less than 27, but the defect estimation is not less than 1.5 times of the actual test result, analyzing a test defect estimation algorithm; and when the evaluation absolute value of the hardware in-loop test result is less than 27 and the defect estimation is less than 1.5 times of the test result, the HIL test is considered to be sufficient and the test can be terminated.
The formula II is as follows:
in the second formula:
n is the number of test modules divided in the test architecture;
λiis the weight of the ith test module.
K1 is a BUG prediction coefficient, and the coefficient is closely related to the complexity of the functional module, the test design maturity and the functional design maturity;
the number of the corresponding test defects of each functional module in actual test is BugRL;
BugNUM is the number of the test defects estimated by each functional module;
and obtaining the estimation of the hardware-in-loop test defects through a second formula.
K1 in equation two is derived from equation three.
The formula III is as follows:
K1＝C1×M1+C2×M2+c3×M3
in the formula three, the constraint condition is that C1+ C2+ C3 is 1,
c1 is function complexity weight;
m1 is function complexity, and is rated according to the function type realized by the function module.
C2 is test design maturity weight;
m2 is test design maturity, rated according to the module's historical test experience and the test designer's experience.
C3 is functional design maturity weight;
m3 is the function design maturity, the historical application experience of the design module and the designer experience rating.
The beneficial effects of the invention are as follows:
(1) by adding the defect estimation algorithm and the defect result measurement criterion of the hardware-in-loop test, the invention can measure the defects of the hardware before the loop test is executed, is favorable for effectively evaluating the test sufficiency and the test quality of the hardware after the loop test is finished, and particularly aims at a newly developed vehicle control system.
(2) The invention compares and analyzes the distribution of the hardware-in-the-loop test defect prediction result with the actual test defect result, and when the error is larger, the method returns to the previous step to adjust the algorithm, and can obtain sufficient and effective test results after a plurality of tests.
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FIG. 1 shows a hardware-in-loop test system for a vehicle control unit according to the present invention;
FIG. 2 is a hardware-in-loop test flow of the vehicle control unit according to the present invention;
FIG. 3 illustrates a hardware-in-the-loop test environment setting of the present invention;
FIG. 4 is a diagram of hardware-in-the-loop test defect evaluation in the present invention.
Detailed Description
The invention will be further elucidated with reference to the drawings and reference numerals.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the embodiments of the present invention, the terms "first", "second", "third", and the like are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.
In the description of the embodiments of the present invention, "a plurality" means at least 2.
In the description of the embodiments of the present invention, it should be further noted that unless otherwise explicitly stated or limited, the terms "disposed," "mounted," "connected," and "connected" should be interpreted broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The following describes in detail embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
Example 1:
as shown in fig. 1, a hardware-in-loop test system for a new energy vehicle controller, the system includes:
host computer, test cabinet and vehicle control unit.
The upper computer is connected with the test cabinet through the Ethernet.
The test cabinet is in communication connection with the vehicle control unit.
The test cabinet comprises a real-time simulation system, the real-time simulation system is used for operating a test model, and the test model comprises: the system comprises a whole vehicle power model, a driving environment model, a road spectrum model, a driver and cab model and a limit working condition model.
And the upper computer is connected with the whole vehicle controller through a calibration observation tool and is used for reading a test operation result.
The vehicle control unit is connected with the test cabinet through a wire harness, and signals transmitted by the wire harness mainly comprise various hard wire signals and CAN wire signals.
Example 2:
as shown in fig. 1 to 4, a hardware-in-loop test system for a new energy vehicle controller includes:
host computer, test cabinet and vehicle control unit.
The upper computer is connected with the test cabinet through the Ethernet.
The test cabinet is in communication connection with the vehicle control unit.
The test cabinet comprises a real-time simulation system, the real-time simulation system is used for operating a test model, and the test model comprises: the system comprises a whole vehicle power model, a driving environment model, a road spectrum model, a driver and cab model and a limit working condition model. The whole vehicle power model comprises a vehicle dynamic model, a driving motor model and a battery model. The main parameters of the vehicle dynamic model comprise the servicing quality, the position of a mass center, the windward area, the radius of a tire, the main reduction ratio and the like; the main parameters of the driving motor model are motor rated/peak power efficiency characteristic data; the battery model mainly comprises charge-discharge characteristic data of monomers with different numbers of series-parallel connection and different temperatures; the driving environment model comprises wind speed, road rolling resistance coefficient, altitude and the like; the road spectrum model comprises various typical working condition data; the driver and cab models are divided into a driver model and a cab model. The driver model simulates the driving habits of different drivers according to the opening information of an accelerator pedal and a brake pedal of a real vehicle road test; the cab model simulates some cab panel signals, so that hardware-in-loop test input is facilitated; the limit condition model is mainly used for quickly and conveniently setting various abnormal fault information.
And the upper computer is connected with the whole vehicle controller through a calibration observation tool and is used for reading a test operation result.
The vehicle control unit is connected with the test cabinet through a wire harness, and signals transmitted by the wire harness mainly comprise various hard wire signals and CAN wire signals.
A hardware-in-loop testing method for a new energy vehicle controller comprises the following steps:
step A: acquiring hardware-in-loop test data of the vehicle control unit, analyzing the hardware-in-loop test requirements, and editing a test requirement matrix analysis list (shown in table 1).
| Test item | Test priority | Correlated analog input signal | Related CAN input signal | Output signal | Related test items | Related details | Criteria for end of test |
| Software and hardware interface | 1 | 45 | 4 | 25 | 3 | 8 | FUN1 |
| Power up and down management | 1 | 12 | 35 | 8 | 2 | 3 | FUN2 |
| Fault management | 2 | 8 | 50 | 6 | 2 | 16 | FUN3 |
| Vehicle operating mode switching | 2 | 4 | 34 | 5 | 4 | 16 | FUN4 |
| Vehicle drive | 2 | 15 | 23 | 8 | 2 | 23 | FUN5 |
TABLE 1
The hardware-in-loop test data of the vehicle controller comprises a control system communication network topology, a vehicle controller communication matrix, a software and hardware interface specification and a vehicle controller function specification.
The step A comprises the following steps: and defining a hardware-in-loop test range, a test function item, a test depth and a test target of the whole vehicle controller in the requirement analysis matrix.
And B, step B: and B, according to the analysis of the hardware-in-loop test requirements, building a hardware-in-loop test environment of the vehicle controller, and according to the limit working condition model built in the step A in the test depth.
The hardware-in-loop test environment comprises a vehicle model, a driving environment model, a road spectrum model, a driver and cab model, a battery model and a motor model.
The step B specifically comprises the following steps:
step B1: and (3) building a hardware-in-loop test environment of the vehicle control unit in modeling software of the upper computer, and compiling.
Step B2: and configuring a network mapping relation of nodes in VeriString test management software of the upper computer and a hard-line signal mapping relation of hardware of the vehicle control unit and the test cabinet according to the network topological structure of the vehicle control unit.
Step B3: and deploying the configured hardware-in-loop test environment of the vehicle control unit into a test cabinet in Veristand software, and simulating the in-loop test environment for running the vehicle control unit in real time by the test cabinet.
And C: and determining a hardware-in-loop test defect estimation algorithm and hardware-in-loop test result evaluation based on the test requirement matrix analysis list and the hardware-in-loop test environment, and generating hardware-in-loop test defect estimation.
The step C specifically comprises
Step C1: compiling a script file by utilizing Python software, identifying a test requirement matrix analysis list and a built test environment of the whole vehicle controller, determining a hardware-in-loop test defect estimation algorithm and a defect result measurement criterion, and calculating hardware-in-loop test defect estimation according to BugNUM;
the formula I is as follows:
BugNUM＝A×λA+(IN1+IN2+OUT)×λPort+MAX{NUM1，NUM2}×λNUM+Ff×λf
in the first formula:
a is the number of related analog input signals;
λAcounting the contribution rate of the number of analog input signals to the number of BUGs for the history;
IN1the number of other hard-line input signals except the analog signal;
IN2number of CAN input signals;
OUT is the number of output signals;
λPORTtesting the contribution rate of the historical statistical interface to the number of BUGs;
NUM1 is the number of relevant test items;
NUM2 is the number of parts associated with the test item;
λNUMtesting the contribution rate of the historical statistical function correlation analysis to the number of BUGs;
ff is the number of the sub-function items of the test item;
λ f history statistics is carried out on the contribution rate of the number of the sub-function items to the number of BUGs;
step C2: and performing hardware-in-loop test defect estimation to generate hardware-in-loop test defect estimation.
Step D: and setting a test framework of the whole vehicle controller, a test case design method of each sub-function, the number of test cases of each sub-function, the priority of test execution and a test interception criterion based on hardware-in-loop test defect estimation.
Step E: performing hardware-in-loop test, specifically comprising the following steps:
and designing the test case according to the set test case design method.
And executing the test case according to the set test execution priority, and recording the execution result of the test case.
And stopping test execution according to the estimated test stopping criterion.
And E, completing the execution of the test case with the highest priority, and if the test case meets the test cutoff criterion, evaluating the hardware-in-loop test execution result.
Step F: hardware was evaluated in the loop test.
And evaluating the hardware-in-loop test of the vehicle controller according to the test case execution result and the hardware-in-loop test result evaluation to obtain a hardware-in-loop test evaluation result.
In the step F, calculating the evaluation BugEval of the in-loop test result of the hardware, and when the evaluation absolute value of the in-loop test result of the hardware is not less than 27, analyzing the setting of the in-loop test environment of the hardware; when the hardware in-loop test result evaluation absolute value is less than 27, but the defect estimation is not less than 1.5 times of the actual test result, analyzing a test defect estimation algorithm; and when the evaluation absolute value of the hardware in-loop test result is less than 27 and the defect estimation is less than 1.5 times of the test result, the HIL test is considered to be sufficient and the test can be terminated.
The formula II is as follows:
in the second formula:
n is the number of test modules divided in the test architecture;
λiis the weight of the ith test module.
K1 is a BUG prediction coefficient, and the coefficient is closely related to the complexity of the functional module, the test design maturity and the functional design maturity;
the number of the corresponding test defects of each functional module in actual test is BugRL;
BugNUM is the number of the test defects estimated by each functional module;
and obtaining the estimation of the hardware-in-loop test defects through a second formula.
K1 in equation two is derived from equation three.
The formula III is as follows:
K1＝C1×M1-tC2×M2+C3×M3
in the formula three, the constraint condition is that C1+ C2+ C3 is 1,
c1 is a functional complexity weight;
m1 is the function complexity, and is rated according to the function type realized by the function module.
C2 is test design maturity weight;
m2 is test design maturity, rated according to the module's historical test experience and the test designer's experience.
C3 is functional design maturity weight;
m3 is the function design maturity, the historical application experience of the design module and the designer experience rating.
Step G: the hardware-in-loop test optimization: and improving the defect evaluation of the hardware-in-loop test or improving the set test environment based on the evaluation result of the hardware-in-loop test.
Step H: and D, repeating the step D to the step F based on an improved hardware-in-loop test defect estimation algorithm until the test evaluation reaches the hardware-in-loop test target.
The invention is not limited to the above alternative embodiments, and any other various forms of products can be obtained by anyone in the light of the present invention, but any changes in shape or structure thereof, which fall within the scope of the present invention as defined in the claims, fall within the scope of the present invention.
Claims (10)
1. The hardware-in-loop test system for the new energy vehicle controller is characterized by comprising the following steps:
the system comprises an upper computer, a test cabinet and a whole vehicle controller;
the upper computer is connected with the test cabinet through an Ethernet;
the test cabinet is in communication connection with the vehicle control unit;
the test cabinet comprises a real-time simulation system, the real-time simulation system is used for operating a test model, and the test model comprises: the system comprises a whole vehicle power model, a driving environment model, a road spectrum model, a driver and cab model and a limit working condition model.
2. The hardware-in-the-loop test system of the new energy vehicle controller according to claim 1, wherein the upper computer is connected with the vehicle controller through a calibration observation tool and used for reading test operation results.
3. The hardware-in-loop test system of the new energy vehicle controller according to claim 2, wherein the vehicle controller and the test cabinet are connected through a wire harness, and signals transmitted by the wire harness mainly comprise various hard wire signals and CAN wire signals.
4. A test method according to any one of claims 1 to 3, comprising the steps of:
step A: acquiring hardware-in-loop test data of the vehicle controller, analyzing hardware-in-loop test requirements, and editing a test requirement matrix analysis list;
and B: according to the analysis of the hardware-in-loop test requirements, establishing a hardware-in-loop test environment of the whole vehicle controller;
and C: determining a hardware-in-loop test defect estimation algorithm and hardware-in-loop test result evaluation based on the test requirement matrix analysis list and the hardware-in-loop test environment of the vehicle control unit, and generating hardware-in-loop test defect estimation;
step D: setting a test framework of the whole vehicle controller, a test case design method of each sub-function, the number of test cases of each sub-function, the priority of test execution and a test interception criterion based on hardware-in-loop test defect estimation;
step E: testing the hardware in a ring, and designing a test case according to the set test case design method; executing the test case according to the test execution priority, and recording the test case execution result; stopping test execution according to the estimated test interception criterion;
step F: evaluating the hardware-in-loop test, namely evaluating the hardware-in-loop test of the vehicle controller according to the test case execution result and the hardware-in-loop test result evaluation to obtain a hardware-in-loop test evaluation result;
step G: optimizing the hardware-in-loop test, and improving the estimation of the hardware-in-loop test defects or improving the set hardware-in-loop test environment based on the evaluation result of the hardware-in-loop test;
step H: and D, repeating the steps D to F based on an improved hardware-in-loop test defect estimation algorithm until the hardware-in-loop test evaluation result reaches the hardware-in-loop test target.
5. The hardware-in-the-loop test system test method of the new energy vehicle controller according to claim 4, characterized in that: in the step a, the hardware-in-loop test data of the vehicle controller includes a control system communication network topology, a vehicle controller communication matrix, a specification of software and hardware interfaces, and a specification of vehicle controller functions.
6. The hardware-in-the-loop test system test method of the new energy vehicle controller according to claim 4, characterized in that: the step A comprises the following steps: and defining a hardware-in-loop test range, a hardware-in-loop test function item, a hardware-in-loop test depth and a hardware-in-loop test target of the whole vehicle controller in the analysis of the hardware-in-loop test requirements.
7. The hardware-in-loop test system test method of the new energy vehicle controller according to claim 6, characterized in that: the step B specifically comprises the following steps:
step B1: building a hardware-in-loop test environment of the whole vehicle controller in modeling software of the upper computer, and compiling;
step B2: according to the network topology structure of the vehicle control unit, configuring the network mapping relation of nodes in VeriString test management software of an upper computer, and the hardware of the vehicle control unit and the hard-line signal mapping relation of a test cabinet;
step B3: and deploying the configured hardware-in-loop test environment of the vehicle control unit into a test cabinet in Veristand software, and simulating the hardware-in-loop test environment of the vehicle control unit to run in real time by the test cabinet.
8. The hardware-in-the-loop test system test method of the new energy vehicle controller according to claim 4, characterized in that: the step C specifically comprises the following steps:
step C1: compiling a script file by utilizing Python software, identifying a test requirement matrix analysis list and a built test environment of the whole vehicle controller, and determining a hardware-in-loop test defect estimation algorithm and a defect result measurement criterion;
step C2: and performing hardware-in-loop test defect estimation to generate hardware-in-loop test defect estimation.
9. The hardware-in-the-loop test system test method of the new energy vehicle controller according to claim 4, characterized in that: in the step E, the test case with the highest priority is executed, and if the test case meets the test cutoff criterion, the hardware-in-loop test execution result is evaluated.
10. The hardware-in-the-loop test system test method of the new energy vehicle controller according to claim 9, characterized in that: in the step F, when the evaluation absolute value of the hardware-in-loop test result is not less than 27, the setting of the hardware in the loop test environment is analyzed;
when the hardware in-loop test result evaluation absolute value is less than 27, but the defect estimation is not less than 1.5 times of the actual test result, analyzing a test defect estimation algorithm;
and when the evaluation absolute value of the hardware in-loop test result is less than 27 and the defect estimation is less than 1.5 times of the test result, the HIL test is considered to be sufficient and the test can be terminated.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020401A (en) * | 2013-01-06 | 2013-04-03 | 北京经纬恒润科技有限公司 | Method, device and system for testing ECU (Electronic Control Unit) |
| CN105511326A (en) * | 2015-12-31 | 2016-04-20 | 北京长城华冠汽车科技股份有限公司 | Calibration system and calibration method for whole automobile controller of electric automobile |
| CN206920121U (en) * | 2017-06-15 | 2018-01-23 | 吉林大学 | A kind of electric mechanical braking booster hardware-in-loop simulation testing stand |
| US20180308296A1 (en) * | 2017-04-25 | 2018-10-25 | GM Global Technology Operations LLC | Emulator hardware-in-loop architecture and control logic for vehicle steer-by-wire test system |
| CN110837231A (en) * | 2019-11-15 | 2020-02-25 | 清华大学 | In-loop simulation method and device and control platform |
| CN110888417A (en) * | 2019-12-16 | 2020-03-17 | 苏州智加科技有限公司 | Real-time simulation and test method for control system of automatic driving truck |
| CN111007840A (en) * | 2019-12-23 | 2020-04-14 | 奇瑞商用车（安徽）有限公司 | Whole vehicle controller hardware-in-loop test platform and method |
| CN111221325A (en) * | 2020-01-20 | 2020-06-02 | 吉利汽车研究院（宁波）有限公司 | Hardware-in-loop test system and method |
-
2020
- 2020-11-10 CN CN202011245231.0A patent/CN114460914B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020401A (en) * | 2013-01-06 | 2013-04-03 | 北京经纬恒润科技有限公司 | Method, device and system for testing ECU (Electronic Control Unit) |
| CN105511326A (en) * | 2015-12-31 | 2016-04-20 | 北京长城华冠汽车科技股份有限公司 | Calibration system and calibration method for whole automobile controller of electric automobile |
| US20180308296A1 (en) * | 2017-04-25 | 2018-10-25 | GM Global Technology Operations LLC | Emulator hardware-in-loop architecture and control logic for vehicle steer-by-wire test system |
| CN206920121U (en) * | 2017-06-15 | 2018-01-23 | 吉林大学 | A kind of electric mechanical braking booster hardware-in-loop simulation testing stand |
| CN110837231A (en) * | 2019-11-15 | 2020-02-25 | 清华大学 | In-loop simulation method and device and control platform |
| CN110888417A (en) * | 2019-12-16 | 2020-03-17 | 苏州智加科技有限公司 | Real-time simulation and test method for control system of automatic driving truck |
| CN111007840A (en) * | 2019-12-23 | 2020-04-14 | 奇瑞商用车（安徽）有限公司 | Whole vehicle controller hardware-in-loop test platform and method |
| CN111221325A (en) * | 2020-01-20 | 2020-06-02 | 吉利汽车研究院（宁波）有限公司 | Hardware-in-loop test system and method |
Non-Patent Citations (2)
| Title |
|---|
| 孙海龙，等: "纯电动汽车电驱动系统硬件在环仿真试验台架开发", 传动技术, vol. 28, no. 4, 30 December 2014 (2014-12-30), pages 19 - 26 * |
| 闫斌，等: "混合动力车辆硬件在环测试系统研究", 系统仿真学报, vol. 29, no. 6, 8 June 2017 (2017-06-08), pages 1237 - 1243 * |
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