Research On SOC Estimation And Balance Control Methods For Power Battery Packs

Due to energy depletion, environmental problem and the serious economic situation, the general strategy of international industry development has focused on the concept of energy-saving, emission-reduction and exploit of new energy resources. Without question the automotive industry is in the spotlight, new energy automobile has become the inevitable developing direction, whoever gains the initiative can establish his leading position in the future auto industry. The technical bottleneck of new energy automobile lies in the research, development and management of high performance power battery, so together with the battery material and structure design, battery management system (BMS) also becomes a popular research area. Based on this background, the management system especially for the rechargeable power battery is carefully studied in this paper, and research contents are listed as follows:Firstly, with consideration of current research, the basic functions of BMS are generally introduced and summarized, including charge/discharge management, state of charge (SOC) estimation, cell balance control inside the battery pack and state of health (SOH) estimation. The common implementation methods and technical difficulties for each function are briefly described.Secondly, as one of the most important function of BMS, SOC estimation is comprehensively and specifically studied. In this section, an equivalent battery model is established in combination with statistical parameter identification strategy, and battery SOC is estimated by adopting constant parameter model, dynamic parameter model, and two dimensional dynamic parameter model respectively; then this electromotive force (EMF) method is combined with ampere hour counting method through a parallel feedback weighting structure; finally, based on TI series digital processor DSP 2407, hardware and software of the system are designed and implemented, experiments are conducted under multiple operating modes; besides, unscented Kalman filter (UKF) is employed as an advanced algorithm to estimate battery SOC, related simulation studies are carried out.Then, to solve the un-uniformity problem of each cell voltage when batteries operate under series-connected condition, a bidirectional non-dissipative battery balancing system is designed and implemented. Battery energy can be transferred from cells with higher voltage to cells with lower voltage through energy storage inductor, so cell balance is realized in this way. Signal processing circuit and balancing circuit are integrated through effective resource allocation in hardware; and in software a high efficient group-balancing strategy is designed to enhance the energy transfer ability of the system.