Research On The Design And SOC Estimation Of Lithiun-ion Battery Management System

With the rapid development of the electric vehicle industry, as the power system of pure electric vehicle, modular large lithium-ion battery pack is widely used. However, the safety and service life of lithium-ion battery pack can not meet the demand for the use of pure electric vehicles. To solve these problems, we need to monitor the external parameters of lithium-ion battery back, in order to achieve the estimation of the internal state of the battery. Then implement effective management of lithium-ion battery pack to improve the efficiency of the battery and prolong battery life. This is the most basic function of Battery Management System(BMS, Battery Management System).As a popular description parameter on state of the battery pack capacity in modern domestic and abroad, the estimation of battery state of charge(SOC, State Of Charge) is an important part of battery management system. The accuracy of SOC estimation is a key in the impact of vehicle control strategy. However, the estimation of SOC is impacted by such as: charge-discharge rate, temperature, self-discharge and cycle life, and many other factors. Therefore, the accuracy of SOC estimation is very difficult to guarantee in practice.Therefore, this paper will launch the research based on the lithium-ion battery management system from the following aspects: First, describe the design of the battery management system on bath hardware and software aspect, based on the full study and master the lithium-ion battery characteristics and battery management system functional requirements. Second, in order to improve the accuracy of the pure electric vehicle lithium battery SOC estimation, the paper designed the SOC estimation strategy based on Kalman filtering method. To implement this method: First, simulate the pure electric car GM-EV1 vehicle model in NYCC and UDDS actual conditions by use the electric vehicle simulation software ADVISOR2002. Acquire the voltage value, current value and the SOC of the lithium-ion battery pack at corresponding condition, and get the curvilinear relationship equation by fitting OCV-SOC curve. Then, create a first-order RC equivalent circuit model of lithium-ion battery and get the circuit relational expression, as the system state equation and system observation equation of Kalman Filter. After that, applicate the battery voltage and current data acquired from the simulation software ADVISOR, and through MATLAB M-file software code written to achieve the five-step recursive operations based on Kalman filter. Finally, obtain the results of the battery pack SOC under different conditions.In the end, analyze the result of the error on the SOC between ADVISOR simulation and Kalman filter algorithm. The results show that the Kalman filtering method in estimating the battery SOC, solute the problem of high initial error and high cumulative error in Ah integration method effectively.