Study on Optimal Shift Schedule for Single-shaft Parallel PHEVs Considering Driver’s Performance Expectation

In order to take into account the drivers’ performance expectations in the comprehensive performance optimization of plug-in hybrid electric vehicles (PHEVs), we proposed an optimization method for the shift schedule of single-shaft parallel PHEVs considering drivers’ demands on both dynamic and economic performance. In accordance with torque distribution strategies developed for different working modes, the modes switching logic is formulated based on the demand torque along with the engine torque characteristics and the state of charge (SOC) of power battery. And a quantification model for driver’s intention is proposed using a fuzzy inference approach, which can compute the driver's dynamic and economic performance expectations using the driver's operation characteristics and vehicle status as input. With the help of a linear weighting method using the performance expectations as weights, a comprehensive performance evaluation function is constructed as the optimization objective of shift schedule. An adaptive particle swarm optimization (APSO) algorithm is then used to formulate a number of personalized optimal shift schedules (POSS) to reflect various drivers’ performance expectations. To evaluate the formulated POSS, a simulation model was built using the MATLAB/Simulink software and simulations under World Light Vehicle Test Cycle (WLTC) using different typical shift schedules were carried out. Simulation results under WLTC using the optimal dynamic, optimal economic and POSS show that, the equivalent fuel consumption (EFC) of the POSS is reduced significantly compared to that of the optimal dynamic shift schedule, which can be saved by 11.8%, and the EFC of the POSS is only increased by 1.7% compared to that of the optimal economic shift schedule, when the initial SOC is 0.9.