Electric Car Battery Power Monitoring Technology Study

At present, from the view of environmental and energy problems, electric vehicles have been developed for it's benefit of zero emission and low noise. Many countries have regarded electric vehicles as main aim of automobile industry. Energy management system is the key technology of electric vehicle. A good energy management system is based on knowing the exact state-of-charge (SOC). In this respect, estimating the state-of-charge is an essential element to the development of electric vehicles.Although the lead-acid battery has many shortages, at present, it still is the main energy to electric vehicles for low price and maturate technics, in particular, the technology of obturation have been perfected. This paper does research on lead-acid battery. First, describes the electrochemistry characteristic of lead-acid battery, point out the factors of affecting residual capacity(RC) and the difficulties of estimating stage-of-charge. Then, the most common techniques for estimating the SOC of electric vehicle's battery in the world are introduced. And the disadvantages of these methods are described, in addition, some research work of our university in this field are introduced. Based on these, this paper raise a new self-tuning fuzzy criterion approach to estimate RC. Check the current and voltage on charge or discharge, use fuzzy control principle and AH approach to estimate the SOC, and correct the actual charge to get the exact result, in this work, a multi-layer feed forward neural paradigm is used for SOC fuzzy estimator design, and a rapid learning algorithm that is realized model structure identification is proposed also, and find the fuzzy principles make use of their massively parallel architecture and learning capacity. This method has accurate determination, and did not need too much data about battery.In addition, this paper describes the design of system's software and hardware, and raises the idea to advance system.