I-SA Algorithm Based Optimization Design and Mode-Switching Strategy for a Novel 3-Axis-Simpson Dual-Motor Coupling Drive System of PEV

Abstract

Pure electric vehicle (PEV) equipped with a dual-motor coupling drive system can make full use of the high efficiency working range of the motor in order to improve vehicle efficiency. In order to further expand the application range of the system and to improve its practical application, this paper designs and proposes a new dynamic coupling drive system of three axis-double working modes, which is based on the Simpson planetary gear train. The new system adopts two planetary gears (P1 and P2), and the two sun gears of double rows, planetary carrier of P1 and gear ring of P2 are bunded. The power output of the P1 gear ring (mode 1) and P2 planetary carrier (mode 2) is realized by a controlling wet clutch. This paper adopts the linear interpolation method, least square method and 5-fold CV cross validation method to establish the full load speed characteristics and efficiency characteristics models of two motors (13 and 30 kW). This paper proposes an optimization design method based on an improved simulated annealing (I-SA) algorithm for new system parameter matching and working mode switching strategy determination. The results show that the modeling accuracy of the two motors is high, and the mean value of MAPE is 4.337%. The proposed optimization design method achieves the demand goal of PEV effectively. The I-SA algorithm has good effectiveness and fast convergence, the mean efficiency of the optimized PEV is 83.91% under all working conditions, the maximum speed is 142.56 km/h and the power utilization rate of the dual-motor is 100%. This study proposes a new hardware system and a design optimization method on software and provides a direct reference for the research of PEV drive systems by combining hardware with software.