Abstract
This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. In low-temperature environments, EVs suffer a sharp driving range loss resulting from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as the temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating the battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then, given a certain ambient temperature, a target preheating temperature is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with decreasing ambient temperature, however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save on total vehicle operation costs.
Highlights
Vehicle-mounted Li-ion power batteries are the only energy supply system of electric vehicles (EVs), with limited electricity stored inside
The little high charged compared to normal battery is because theaccording temperature and9.current rate of optimization results given by NSGA-II indicate that the optimal preheating target temperature is 2 battery keep changing over a wide range in the driving cycle, which accelerates battery degradation
This paper presents a novel preheating management strategy aimed at lowering the total operation cost of an electric vehicle
Summary
Vehicle-mounted Li-ion power batteries are the only energy supply system of electric vehicles (EVs), with limited electricity stored inside. With no need to solve the complicated thermal-electrochemical equations, these proposed models directly calculate the heat generation rate from the internal resistance, improving its applicability in the battery management system (BMS) of electric vehicles due to its computationally efficiency. A great variety of optimization methods have been applied successfully to various engineering battery management optimization problem, whichgood undeniably provided a competent problems in automotive applications, achieving performance Optimization tools such solution as fuzzy but made the optimization process complicated with too manymethods state equations involved. Questions:utilized (1) how to establish a principle comprehensive battery model automotive analysis; (2) how Pontryagin’s maximum (PMP) to solve the thermal andfor energy battery management to quantify the cost of vehicle operation;.
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