Research On Estimation Of SOC And Software Design For Battery Management System

The battery management system (BMS, battery management system) real-time monitor the parameters of the power battery voltage, current, temperature, the remaining capacity and cycle life, and through the result of the test to balanced control the battery,to report the parameters of the battery and the system alarms for the control system of the vehicle, under the premise to ensure the safety of the battery,it can effectively improve the efficiency of the battery and reduce the operating costs.The estimation of state of charge (SOC) is an important part of the BMS, as one of the vehicle’s control strategy standards, but the estimation of the SOC is influenced by many factors (such as the charge and discharge rate, ambient temperature, cycle life, self-discharge and so on), at the same time, due to complex automotive operating conditions, it is difficult to guarantee the accuracy of the estimation of the SOC in the practical application.This paper combined the special of the battery management system, deeply analyzed reason why the estimation of SOC is difficult to achieve a higher accuracy and the relevant method of estimation of SOC. In the environment of Matlab\Simulink,we conducted a simulation analysis of the open circuit voltage, Amper-Hour integral method, Kalman filtering method and estimation of SOC,based on simulation results, put forward the method to refine the battery,use the combination of the Amper-Hour integral and the open circuit voltage measurements and based on the factors of compensation error of the estimation of SOC. On one hand, The program solved the disadvantages of open circuit voltage, Amper-Hour integral method, on the other hand, the introduction of impact factors will continue to calibrate the total battery capacity and available capacity, it has the advantages of initialing error and accumulating error, but there is no need to build a complex model of the battery, avoids the high dependence to the model of the battery in the Kalman filtering method, it greatly reduced the computational complexity of the system and reduced the speed of data processing.This paper made the overall design and implementation, and completed modular division for the software system of BMS, and made the program design for driver layer, protocol layer and application layer of each module, on the system test platform, conduct an experiment of the battery’s characteristics, offline deposit the test results in the module of SOC estimation as the error-corrected impact factor. We verifier the system functions and the accuracy of SOC estimation in a simulated operating conditions, the results show that the every functional module of the system is stable and reliable, the SOC estimation accuracy meet the standard of designation.