Simulation and Multi-Objective Optimization of the Vehicle Thermal Management System of Electric Cars

Abstract

The research on the vehicle thermal management (VTM) system is very important for ensuring the driving reliability of electric cars, however, currently there’re few research concerned about this topic, and the existing ones mostly focus on matching and optimizing parameters to improve the management of driving kinetic energy, and the heat dissipation and cooling performance of the cars; however, there isn’t a uniform standard for evaluating these performances, and the research on closed thermal energy management and control based on the evaluation results is pending. This paper studied the simulation and multi-objective optimization of the VTM system of electric cars, and proposed accurate methods and ideas for evaluating the heat dissipation efficiency of the engine cooling system, the cooling efficiency of the air conditioning system, and the thermal management performance of the VTM of electric cars. Based on the model predictive control (MPC) algorithm of vehicle motion control, this paper constructed temperature control optimization objective functions for electric cars under various thermal adaptation working conditions such as low-speed slope climbing, medium-speed gentle slope climbing, high-speed driving, and idling; and it designed several strategies for the coordinated control of the VTM system of electric cars. At last, this paper used test results to verify the effectiveness of the proposed strategies.

Dynamic scheduling algorithm of electric vehicles based on smart grid

“…The construction and development of smart grid will not only automate, informatize, interact with, and intelligentize all aspects of power generation, transmission, distribution, substation, consumption, and dispatch, but also accelerate the construction of a modern power grid with a high degree of integration of "power flow, information flow, and business flow" in China [8].…”