Research On Battery Monitoring System For Lithium-ion Cell Pack Of Electric Vehicles Based On MC9S12 Microcontroller

Lithium-ion battery has been paid more attention in the electric vehicle industry for its virtues, such as small size, high energy density and long life. But when used in group, lithium-ion battery has problems such as overcharge and over discharge, the problem of imbalance, which would affect the battery application performance, shorten the battery life. If handled improperly, the lithium-ion battery would on fire, explosion, which would endanger the safety of personal and property of occupants. The battery monitoring system is meaningful in lithium-ion battery application.In this paper, a battery monitoring system based on MC9S12 has been developed, and experimental research related been conducted, the system is made up of hardware circuit, the SOC estimation algorithm, and control subsystem. The hardware circuit consists of the acquisition circuit for voltage, current, and temperature, the equalization circuit, the communication circuit. The SOC estimation algorithm based on Open Circuit Voltage and Ampere Hour method, the initial SOC be calculated by the improved Open Circuit Voltage method, which consider the influence of the dynamic hysteretic characteristic, improve the estimation accuracy of the initial SOC; the real time SOC is calculated by the improved Ampere Hour method, which considers the influence of the coulomb efficiency experiments, adopting high precision current acquisition scheme, improve the accuracy. On control system, the master-slave control made has been chosen. It was actuated by an embedded controller, which was developed based on an HCS12 microprocessor, and functions be write according to the requirement of the system. The PC control software has been written based on Lab VIEW, which include environmental monitoring, information display, series communication modules.The prototype has been made and a series of experimental studies has been conducted, including the acquisition of battery information, the equalization control, and the SOC estimation algorithm. Experimental results show that the robot can correctly accomplish the function of battery monitoring system, the whole system is stable and reliable.