Support vector machine based soc estimation for electric vehicles

A support vector machine approach is used to estimate the battery's state of charge of the electric vehicles. According to a battery is a nonlinear system, nonlinear support vector machines with polynomial kernel and radial basis function kernel are developed for the estimation of the state of charge with least square support vector machine algorithm. For the goal of practice, the paper gives the simplified method to decrease the estimator's complexity. The results have showed that the estimator with polynomial kernel is less accurate but more agreeable to application, the estimator with radial basis function kernel is more accurate but less agreeable to use. One can select optimal kernel to improve the performance of estimation in practice.