Estimation Method of State of Charge of Power Battery of New Energy Vehicle Based on K Nearest Neighbor Regression

In order to improve the power battery state of charge detection ability of new energy vehicles and reduce harmonic interference, a measurement method of power battery state of new energy vehicles based on K-nearest neighbor regression analysis is proposed. Build a charging state parameter collection model of new energy vehicle power battery, consider the unbalanced power of uncertain factors, realize the oscillation and fusion processing of charging state of new energy vehicle power battery through the dynamic matching method of mobile energy storage resources of electric vehicle, extract the microgrid load fluctuation characteristic value of charging state signal of new energy vehicle power battery, and analyze the percentage of remaining electricity to rated capacity. The initial charge and capacity characteristics of the battery of the new energy vehicle power battery are matched. The K-nearest neighbor regression analysis method is used to realize the regression analysis and dynamic estimation of the battery state of charge parameters. According to the state of charge of the new energy vehicle power battery, the steady-state characteristic quantity is output, and the demand response load model parameter reconstruction and load balance matching method are used to realize the state of charge estimation and parameter adaptive evaluation of the new energy vehicle power battery. The simulation results show that the accuracy of measuring the state of charge of the power battery of new energy vehicles is high, and the harmonic suppression ability is strong, which improves the balanced configuration and load balancing scheduling ability of the power system of the power battery of new energy vehicles.