辅助混合动力电动汽车技术研究（Ⅶ）——混合动力电动汽车电池荷电状态估计

基金项目:

北京市教委重点项目（P050501-02）.

详细信息

Study on the Technology of Auxiliary-hybrid Electric Vehicle(Ⅶ): Estimating the State of Charge of Battery Pack in Hybrid Electric Vehicles

College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100022, China

摘要: 为了对混合动力电动汽车用电池组荷电状态进行精确估计,减少电量累积方法前期试验的工作量和运行中的误差累积,研究和应用了卡尔曼滤波法.在电池等效电路模型的基础上,建立了电池组系统的状态方程和测量方程,根据汽车运行时对电池电流和电压的实时检测数据,通过滤波算法估计模型中的开路电压,并由此计算电池组的荷电状态.实验表明,卡尔曼滤波在电动汽车电池组荷电状态估计方面具有应用潜力.
- 荷电状态 /
- 等效电路模型 /
- 开路电压 /
- 卡尔曼滤波
Abstract: To accurately estimate the state-of-charge of battery pack in hybrid electric vehicles,to reduce the experimental work before application of the Ampere hour counting method,and to eliminate the accumulation of errors,the Kalman filter is developed to application.Based on the equivalent circuit model of the battery pack,the dynamic state and measurement equations are established,by processing the data collected from the current and voltage of battery pack in real vehicle testing.The algorithm developed by using Kalman filter can estimate the open circuit voltage of battery pack,then state of charge can be calculated.It indicates that Kalman filter has potential for estimating state of charge of batteries in electric vehicles.
- state of charge /
- equivalent circuit model /
- open circuit voltage /
- Kalman filter

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