Research On Battery State Of Charge Estimation Strategy For Extended Range Electric Vehicles

With the improvement of people's living standards, vehicles have already become an indispensable part in our daily life. Although vehicles bring us lots of convenience, they accelerate the consumption of petroleum resources, which aggravate the pollution to the environment. In order to meet human needs, and to reduce the consumption of petroleum resource as well as the dependence on oil resources, Renewable energy vehicles have been invented by people to replace the traditional internal combustion vehicle. Electric Vehicle(EV) is famous for its zero-pollution and zero-emission performance, which is a typical representative of renewable energy vehicle. However, the promotion of EV have been blocked due to the moribund battery technology. Hence, range extended electric vehicles, which is a solution between conventional vehicles and electric vehicles, have have been growing fast during these years.There are three core technologies of range extended electric vehicles:battery technology, energy management technology and motor control technology. In this paper, as to the energy management technology, a kind of battery state of charge (SOC) estimation strategy based on Kalman filtering and Wavelet transform have been proposed, as well as a BMS battery management system have been designed.Firstly, considering the application of the extended range electric vehicle, a Thevenin battery equivalent circuit model is proposed. Constant current discharging and constant current pulse discharging experiment have been conducted to verify the parameters based on Thevenin model.Secondly, this paper introduced wavelet-transform-based Kalman filtering estimation theory. The theory use noise reduction characteristics of multi-scale wavelet transform to denoise the general threshold of BMS signal. Then use the Kalman iterative recursion filtering to estimate performance of SOC estimation strategy. In order to verify the feasibility of estimation strategy, a simulation model of the the proposed SOC estimation strategy have been established in the ADVISOR software, UDDS model was adopted to verify the effectiveness of the proposed SOC strategy in this paper.At last, the paper designed a BMS battery management system which consists of a main control module and a sampling module. The main control module uses MC9S12XEP100 as the main control chip, which is responsible for data processing and communication; Acquisition module uses AD7280A as the main control chip, which is mainly responsible for the collection of single battery voltage, battery monomer battery temperature and the total input and output current.