Credibility evaluation of hardware-in-the-loop simulation systems

Fang, Ke; Zhou, Yiming; Ma, Ping; Yang, Ming

doi:10.1109/ccdc.2018.8407782

Cited by 12 publications

(4 citation statements)

References 10 publications

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“…New software models designed during simulation can quickly and easily be tested on the HIL testbed. Compared to real-world experiments, hardware-in-theloop simulation is characterized by a lower cost, as well as higher safety and reusability [1,2]. The HIL setups reported in the literature for EVs fall under the signal-level, power-level, and mechanical-level categories [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Design and Experimental Evaluation of a Scaled Modular Testbed Platform for the Drivetrain of Electric Vehicles

Kardasz

Kazerani

2023

Vehicles

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Electric vehicles (EVs) are experiencing explosive growth in public adoption, causing a major shift in research and development priorities by OEMs toward electrified powertrains. To verify EV drivetrain platforms and software models in the design phase, testbeds with specific capabilities are essential. Full-scale vehicle testbeds are expensive, bulky, dissipative, and not easily reconfigurable or movable, making scaled testbeds more attractive, especially for education and research institutes. To support this cause, this paper reports on the development of a small-scale, modular, hardware-in-the-loop (HIL) testbed platform for the drivetrain of EVs that is cost-effective, efficient, and easily movable and reconfigurable and allows integration of a battery pack. The testbed is comprised of two directly coupled electric machines. The first machine emulates the traction motor and is used to control vehicle speed according to a specified drive cycle. The second machine is used to impose a torque profile on the first machine’s shaft—based on the vehicle’s parameters and driving environment—and emulates a gearbox (if necessary). A systematic two-way scaling approach is adopted to downscale the parameters and driving environment of full-size EVs to a level that can be handled by the testbed and to upscale the test results obtained from the testbed to the full-size vehicle level. The power consumption of the testbed is limited to system losses. A case study involving a full-size EV was performed and the HIL simulation results were compared to the computer simulation results to verify the performance of the testbed.

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Section: Introductionmentioning

confidence: 99%

Design and Experimental Evaluation of a Scaled Modular Testbed Platform for the Drivetrain of Electric Vehicles

Kardasz

Kazerani

2023

Vehicles

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show abstract

“…Numerical simulation methods face challenges in acquiring annotated data, relying on incorrect domain knowledge, and being limited by data quality issues. Therefore, some scholars have started to establish simulation platforms for Intelligent Connected Vehicles [13,16,17]. These platforms utilize embedded systems, real-time decision-making platforms, control strategies [18], and vehicle dynamics and address data acquisition challenges for special conditions while also addressing emergency communication [19].…”

Section: Introductionmentioning

confidence: 99%

Using Case and Error Analysis on Inspection Methods of Modeling Platforms for Automatic Emergency Call Systems Based on Generated Satellite Signals

Fu,

Ni,

Yang

et al. 2023

Vehicles

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The positional deviation of the in-vehicle Automatic Emergency Call System (AECS) under collision conditions brings difficulties for Intelligent Connected Vehicles (ICVs) post rescue operations. Currently, there is a lack of analysis on system operating conditions during collisions in the reliability assessment methods for the Global Navigation Satellite System (GNSS) deployed in the AECS. Therefore, this paper establishes an in-vehicle collision environment simulation model for emergency calls to explore the influence of parameters such as temperature and vibration on Signal-Based In-Vehicle Emergency Call Systems. We also propose environmental limits applicable to comprehensive tests, which can objectively evaluate reliability and provide data support for the AECS bench test through a satellite-signal-based semi-physical simulation, which is subjected to a bench test under different operating conditions. The findings of this study demonstrate that the occurrence of random vibration and impact stress, induced by vibration, exerts considerable disruptive effects on positional signal data during collisions. Consequently, it leads to substantial interference with the accurate detection of post-collision satellite positioning information. When the simulation operates under a 2.4 gRMS vibration condition, the maximum phase noise error in the positioning system is 8.95%, which does not meet the test accuracy requirements. On the other hand, the semi-simulation system is less affected by temperature changes, and at the maximum allowable temperature difference of the equipment, the maximum phase noise error in the simulated signal is 2.12%. Therefore, based on the influence of phase noise variation on the accuracy of the satellite signal simulation, necessary environmental conditions for the test are obtained, including a temperature that is consistent with the maximum operating temperature of the vector generator and a vibration power spectral density (PSD) lower than 1.2 gRMS.

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“…Numerical simulation methods face challenges in acquiring annotated data, relying on incorrect domain knowledge, and being limited by data quality issues. Therefore, some scholars have started to establish simulation platforms for Intelligent Connected Vehicles [13,16,17]. These platforms utilize embedded systems, real-time decision-making platforms, control strategies [18], vehicle dynamics, and address data acquisition challenges for special conditions while also addressing emergency communication [19].…”

Section: Introductionmentioning

confidence: 99%

Use Case and Error Analysis of Inspection Methods of Modeling Platform for AECS Based on Generated Satellite Signals

Fu¹,

Fang²,

Ni³

et al. 2023

Preprint

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The positional deviation of the Automatic Emergency Call System (AECS) under collision conditions brings difficulties for post-rescue operations. Currently, there is a lack of analysis on the system operating conditions during collisions in the reliability assessment methods for the Global Navigation Satellite System (GNSS) deployed in AECS. Therefore, this paper establishes an in-vehicle collision environment simulation model for emergency calls to explore the influence of parameters such as temperature and vibration on the data deviation of the simulated GNSS system. We also propose environmental limits applicable to comprehensive AECS tests, which can objec-tively evaluate the reliability of AECS and provide data support for AECS bench test. Through the satellite signal-based semi-physical simulation, AECS is subjected to bench test under different operating conditions. The findings of this study demonstrate that the occurrence of random vibra-tion and impact stress, induced by vibration, exerts considerable disruptive effects on positional signal data during collisions. Consequently, it leads to substantial interference with the accurate detection of post-collision satellite positioning information. When the simulation operates under a 2.4gRMS vibration condition, the maximum phase noise error in the positioning system is 8.95%, which does not meet the AECS test accuracy requirements. On the other hand, the semi-simulation system is less affected by temperature changes, and at the maximum allowable temperature dif-ference of the equipment, the maximum phase noise error in the simulated signal is 2.12%. Therefore, based on the influence of phase noise variation on the accuracy of satellite signal simulation, nec-essary environmental conditions for AECS test are obtained, including the temperature consistent with the maximum operating temperature of the vector generator and the vibration Power Spectral Density (PSD) lower than 1.2gRMS.

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Credibility evaluation of hardware-in-the-loop simulation systems

Cited by 12 publications

References 10 publications

Design and Experimental Evaluation of a Scaled Modular Testbed Platform for the Drivetrain of Electric Vehicles

Design and Experimental Evaluation of a Scaled Modular Testbed Platform for the Drivetrain of Electric Vehicles

Using Case and Error Analysis on Inspection Methods of Modeling Platforms for Automatic Emergency Call Systems Based on Generated Satellite Signals

Use Case and Error Analysis of Inspection Methods of Modeling Platform for AECS Based on Generated Satellite Signals

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