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An Optimal Torque Distribution Strategy for Four-Motorized-Wheel Electric Vehicle Considering Energy Conversation

Ying Xu, Lunyao Jiang, Bo Wei, Li Qiu

2020IEEE Access18 citationsDOIOpen Access PDF

Abstract

In this paper, an optimal torque distribution strategy (OTDS) for four-motorized-wheel electric vehicle (4MWEV) is proposed aiming at improving the tractive efficiency and braking energy recovery performance. Based on the motor efficiency map, the objective functions of tractive efficiency and braking energy recycling are established first. Under driving conditions, genetic algorithm (GA) is proposed to obtain the optimal torque distribution ratio of front and rear axles considering the constraints of motor characteristics and desired torque. During braking conditions, an exhaustive search method (ESM) is proposed to improve the energy recovery performance considering the constraints of motor characteristics, battery, braking theory and ECE Regulations. For the realization of efficient and accurate computation, a control scheme of off-line optimization and on-line allocation based on the optimal torque distribution ratio map is presented, which stores the optimal ratios in all available motor operating regions into two-dimensional lookup tables. Finally, co-simulation experiments based on MATLAB/Simulink and Carsim are conducted to verify the effectiveness of the proposed OTDS under NEDC and UDDS driving cycles. Comparing to the typical torque distribution strategy (TTDS), the simulation results demonstrate that the proposed OTDS can enhance the energy-saving performance by 7.01% under NEDC and 6.69% under UDDS.

Topics & Concepts

Computer scienceCarSimTorqueAutomotive engineeringControl theory (sociology)MATLABDriving cycleBattery electric vehicleElectric vehicleVehicle dynamicsEngineeringPower (physics)Control (management)Artificial intelligenceThermodynamicsQuantum mechanicsOperating systemPhysicsElectric and Hybrid Vehicle TechnologiesElectric Vehicles and InfrastructureAdvanced Battery Technologies Research