Cao, Xiliang (Wuhan University of Technology), Du, Changqing (Wuhan University of Technology), Yan, Fuwu (Wuhan University of Technology), Xu, Hongming (University of Birmingham), He, Biao (Wuhan University of Technology), Sui, Yanfeng (Wuhan University of Technology)

Parameter Optimization of Dual Clutch Transmission for an Axle-Split Hybrid Electric Vehicle

Scheduled for presentation during the Regular Session "Modeling & Control: Powertrain" (WeAT2), Wednesday, June 26, 2019, 12:10−12:30, Chenonceau

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on April 16, 2024

Abstract

Abstract: This paper reports the design optimization for a dual clutch transmission (DCT) of a multi-mode axle-split hybrid electric vehicle (HEV). The purpose of optimization is to minimize the equivalent fuel consumption of automobile power demand. The variables that need to be optimized are gear ratio and Shifting threshold value. The optimization is based on a co-simulation platform, in which, the HEV is modelled in LSM Amesim and the control/optimization algorithms are programmed in MATLAB/ Simulink. In this study, the Hybrid Particle Swarm Optimization (HPSO) algorithm is used to solve the optimization problem, which has better global and local search capability comparing with conventional PSO algorithm. The simulation results show that the optimized transmission parameters can guarantee the power demand and have a good fuel economy.