title: A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles.
abstract: Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists.
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. xujun018@gmail.com.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China. xujun018@gmail.com.
authors.forename: Jun
authors.initials: J
authors.lastname: Xu
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. jwang@mail.xjtu.edu.cn.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China. jwang@mail.xjtu.edu.cn.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. lishiying0927@stu.xjtu.edu.cn.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China. lishiying0927@stu.xjtu.edu.cn.
authors.forename: Shiying
authors.initials: S
authors.lastname: Li
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. cbg@mail.xjtu.edu.cn.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China. cbg@mail.xjtu.edu.cn.
authors.forename: Binggang
authors.initials: B
authors.lastname: Cao
keywords: battery management systems; battery model; electric vehicle; fault detection; proportional integral observer; state of energy estimation