Research On State Of Charge Estimation Of Power Battery And The Management System Design

As a indispensable modern device of Hybrid Electric Vehicle(HEV), battery management system(BMS) is developing rapidly both at home and abroad. It can complete the real-time monitoring of battery state (voltage, temperature, charge and discharge current and remaining capacity) in HEV system, and estimating the State of Charge(SOC) of battery is one of the main functions of battery management system.In order to accurately predict the SOC, we combine the ampere-hour method and open-circuit voltage method and Kalman filtering, at the same time take the influence factors of SOC such as temperature and Hysteresis into account, a new prediction algorithm of SOC is put forward in this paper. By means of building the Second order dynamic model of the battery and employ Double Unscented kalman filter(DUKF) to estimate both the state and parameters of the model, let the estimate of SOC reach a higher accuracy. Battery management system can avoid the phenomenons such as overcharge, overdischarge and overheating at work, so that it can improve the life of battery by monitoring the state of battery. This system takes AT89C52microcontroller as the core to control the power quality management chip DS2438and periphery circuit and combine with the algorithm to realize a accurate measurement of battery voltage, current and capacity. The temperature of the battery is measured by a digital temperature sensor known as DS18B20which under the control of AT89C52. Measuring data will be displayed on the panel by LED and the information under the circumstances of power drop can be stored in this system with AT24C02, and it can communicate with the host computer through RS232serial communication interface and can receive the commands of the host at the same time.Finally, estimated the parameters of battery model and the relation curve of open circuit voltage an SOC by discharge experiment, and use matlab simulation to prove the accuracy of DUKF. The experiment results show that the BMS for the measurement of battery voltage and current and the estimating of SOC are reliable.