CAJ | 학술논문

针对电池荷电状态（ SOC ）容易受到电流、温度、循环寿命等非线性因素的影响，建立基于温度和电流变化的电池容量修正方程。结合安时法和复合电化学原理构建电池状态空间模型。由于粒子滤波算法对非高斯、非线性系统的适应性，因此选用粒子滤波算法来研究电池SOC估计。通过美国FTP-75工况和NEDC工况实验仿真显示，基于粒子滤波算法的电池SOC估计比扩展卡尔曼滤波算法估计精度高、适应性好。
침대전지하전상태（ SOC ）용역수도전류、온도、순배수명등비선성인소적영향，건립기우온도화전류변화적전지용량수정방정。결합안시법화복합전화학원리구건전지상태공간모형。유우입자려파산법대비고사、비선성계통적괄응성，인차선용입자려파산법래연구전지SOC고계。통과미국FTP-75공황화NEDC공황실험방진현시，기우입자려파산법적전지SOC고계비확전잡이만려파산법고계정도고、괄응성호。
In view of the many nonlinear factors such as current , temperature, cycle life and so on , it establishes the batter capacity correction equation for state of charge ( SOC ) based on temperature and current .Combining ampere-hour method and composite electrochemical principle , it builds the battery state space model .Based on the adaptability of non-Gaussian and nonlinear system , it applies particle filter algorithm for battery SOC esti-mation.According to the simulation experiments of FTP -75 and NEDC working condition , particle filter algo-rithm estimation precision and adaptability of battery SOC are better than the result of extended Kalman filter al-gorithm.