Design And Development Of Battery Management System For Electric Vehicle

The environmental and economical issues with transportation have accelerated the development of electric vehicles.Amongst the most prominent advantages of energy density and power within this field is the usage of lithium-iron phosphate battery.Supported by the project on JYLF320 electric vehicle, a set of battery management system(BMS) is designed and developed, which has certain theoretical value and practical value for extending service life of battery pack.Experiments on batteries are done to research on lithium-iron phosphate batteries'discharging characteristics based on the designed test bench.The test results reveal that lithium-iron phosphate batteries'discharge process can be divided into three different stages——beginning, platform and ending. During the platform stage, voltage drops very slowly; different discharge rate has little influence on battery capacity while temperature has significantly impacted capacity. Combined with BMS application environment, the structure of BMS is designed, which is devided into five modules——data acquisition module, state monitoring and alarm module, SOC estimation modules, fault diagnosis module and communication module.A new SOC estimation algorithm is proposed, combining Coulomb gauging approach, available capacity correction and SOC correction, which is suitable for the real car use. Correctting available capacity is completed at the time of vehicle periodic maintenance, SOC is changed to value 1 when the voltage rises to the charge end while SOC is changed to value 0 when the voltage drops to the discharge end in order to eliminate accumulative error.Research on the reason of battery performance degradation, the influence of cells'inconsistency on battery pack is needed to determine the method of fault-diagnosis. According to the relationship between the internal degradation mechanism and the external performance, fault-diagnosis method——on-board diagnosis and artificially test diagnosis is presented. On-board diagnosis operates during driving by the cells'correction actual capacity, cells'correction actual capacity by the end of platform and cells'voltage while artificially test diagnosis evaluates the battery technology condition during periodic maintenance according to available capacity,the cells'voltage and temperature difference between adjacent cells'shell. Aiming to overall design of the EV project, a master-slave structure of battery management system is designed and developed, including hardware and software, which is installed to JYLF320 EV. Results of the preliminary operation test show that the system meet the requirements of BMS and the algorithm of SOC estimation battery fault diagnosis effect is reliable.