Abstract
This paper aims to explore torque optimization control issue in the turning of EV (Electric Vehicles) with motorized wheels for reducing energy consumption in this process. A three-degree-of-freedom (3-DOF) vehicle dynamics model is used to analyze the total longitudinal force of the vehicle and explain the influence of torque vectoring distribution (TVD) on turning resistance. The Genetic Algorithm-Particle Swarm Optimization Hybrid Algorithm (GA-PSO) is used to optimize the torque distribution coefficient offline. Then, a torque optimization control strategy for obtaining minimum turning energy consumption online and a torque distribution coefficient (TDC) table in different cornering conditions are proposed, with the consideration of vehicle stability and possible maximum energy-saving contribution. Furthermore, given the operation points of the in-wheel motors, a more accurate TDC table is developed, which includes motor efficiency in the optimization process. Various simulation results showed that the proposed torque optimization control strategy can reduce the energy consumption in cornering by about 4% for constant motor efficiency ideally and 19% when considering the motor efficiency changes in reality.
Highlights
The energy crisis and environmental pollution are important issues for all countries in the world currently, while the automobile industry is one of the iconic industries of social development and technological progress
Wang et al [9] presented a torque vectoring distribution (TVD) control strategy based on recursive least squares (RLS) identification of tire longitudinal stiffness, which effectively reduced the average slip rate of the drive shaft and improved the cornering efficiency
Considering the actual operating conditions of the vehicle, the optimal torque distribution (OTD) coefficient based on motor working points is obtained through simulation analysis, greatly reducing vehicle energy consumption in corners
Summary
The energy crisis and environmental pollution are important issues for all countries in the world currently, while the automobile industry is one of the iconic industries of social development and technological progress. TVD technology applied in 4WID-EVs can greatly reduce the energy consumption of the entire vehicle in corners, improving energy conservation [1,2]. Wang et al [9] presented a TVD control strategy based on recursive least squares (RLS) identification of tire longitudinal stiffness, which effectively reduced the average slip rate of the drive shaft and improved the cornering efficiency. Wong proposed a Holistic Corner Controller (HHC) suitable for 4WID-EVs, using motor MAP directly, according to the instantaneous operating point of the motor, which improved the driving efficiency of the vehicle in various working conditions effectively [12]. Considering the actual operating conditions of the vehicle, the optimal torque distribution (OTD) coefficient based on motor working points is obtained through simulation analysis, greatly reducing vehicle energy consumption in corners. Through the hardware-in-the-loop test, the accuracy of the control strategy proposed in this paper is verified
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