Design of Model-based VCU Software for Driving Performance Optimization of Electric Vehicle

This study designed a model-based Vehicle Control Unit (VCU) software for electric vehicles. Electric vehicles have transitioned from conventional powertrains (e.g., engines and transmissions) to electric powertrains. The primary role of the VCU is to determine the optimal torque for driving control...

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Bibliographic Details
Published inJournal of information and communication convergence engineering Vol. 21; no. 4; pp. 351 - 358
Main Authors Changkyu Lee, Youngho Koo, Kwangnam Park, Gwanhyung Kim
Format Journal Article
LanguageKorean
Published 2023
Subjects
ANN
Model-based Software
Electric Vehicle
VCU
Torque Control
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Summary:This study designed a model-based Vehicle Control Unit (VCU) software for electric vehicles. Electric vehicles have transitioned from conventional powertrains (e.g., engines and transmissions) to electric powertrains. The primary role of the VCU is to determine the optimal torque for driving control. This decision is based on the driver's power request and current road conditions. The determined torque is then transmitted to the electric drive system, which includes motors and controllers. The VCU employs an Artificial Neural Network (ANN) and calibrated reference torque to enhance the electric vehicle's performance. The designed VCU software further refines the final reference torque by comparing the control logic with the torque calculation functions and ANN-generated reference torque. Vehicle tests confirmed the effective optimization of vehicle performance using the model-based VCU software, which includes an ANN.
Bibliography:KISTI1.1003/JNL.JAKO202302272023516
ISSN:2234-8255
2234-8883