Study On State Of Charge Estimation And Equalization Technique Of Electric Vehicle Battery

Eleclric vehicle industry as a focus on the development of strategic emerging industry in China, is an urgent task to deal with our energy and environmental challenges, promote the transformation and upgrading of traditional auto industry, also is strategic move to speed up economic development mode shift. This topic in view of the main constraining factors of the current rapid development of electric vehicles(Power battery management system), to study on the battery state of charge(SOC) estimation and design of battery management system and equalization technology.When a lithium-ion power battery is used in an electric vehicle, the SOC displays a very strong time-dependent nonlinearity under the influence of random factors, such as the working conditions and the environment. Hence, research on estimating the SOC of a power battery for an electric vehicle is of great theoretical significance and application value.Under the condition of off-line parameters are known, propose the segmentation correction method of lithium battery SOC estimation based on the SOH and offline data. The research ideas of segmented correction method: ampere-hour integral method is commonly used for SOC estimation in the engineering, in the process of application, the difficulty is cumulative error elimination in the process of integral. In this paper, firstly, battery state of health(SOH) has been used to estimate the actual usable capacity of the current time, as the divisor of Ah integral method, to correct the SOC estimation. Secondly, the off-line data are used to segmented eliminate the cumulative error of Ah integral method. The simulation results show that,the proposed method has higher accuracy than the traditional Ah integral method, Can better eliminate the cumulative error.Under the condition of off-line parameters are unknown, propose the joint estimation method based on least squares(LS) and the Kalman filter algorithm. The research ideas of joint estimation method: according to the dynamic response of the power battery terminal voltage during a discharging process, the second-order RC circuit is first used as the equivalent model of the power battery. Subsequently, on the basis of this model, the least squares method(LS) with a forgetting factor and the adaptive unscented Kalman filter(AUKF) algorithm are used jointly in the estimation of the power battery SOC. Simulation experiments show that the joint estimation algorithm proposed in this paper has higher precision and convergence of the initial value error than a single AUKF algorithm.Cell balancing plays an important role in preserving the life of series-connected battery packs. By using the theory of inductive energy storage, this paper proposes two novel voltage equalization circuits based on dynamic adjustment of the equalization path and of the equalization threshold.These two kinds of novel circuits are called battery equalization circuit based on multiple criteria defined and battery equalization circuit based on Hierarchical strategy, both equalization circuit consists of several balancing sub-circuits. The equalization circuit based on multiple criteria defined can be used to the battery with small single number, and the equalization circuit based on hierarchical strategy can be used to the battery with large single number. The simulation and experiment results demonstrate that the proposed circuits, which feature a simple control method, fast balancing, and a large equalization current, exhibit outstanding equalization performance.