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Abstract
¡¡¡¡As the mainstream vehicle of modern society, vehicles are widely used in all walks of life. While it brings convenience to people's lives, the emission of automobile exhaust has brought some pressure to the environment at the same time. In view of this situation, New energy vehicles with advantage of zero emissions and slight pollution come into people's attention gradually . In the development of new energy vehicles, the electric vehicles has become the focus of research in the current industry.
¡¡¡¡Lithium battery has been widely used as a power source for electric vehicles because of its high energy density, voltage stability, safety, long service life, and very friendly to environment. The battery as the power supply source of pure electric vehicles, the key technology such as vehicle real-time estimation of battery capacity ,battery fault detection and battery safety problems are to be solved and improved in process of car driving.
¡¡¡¡Battery capacity estimation is the key technology module in the battery management system of electric vehicle. It is significant to improve the battery life and the performance of the whole vehicle by estimating the capacity of battery accurately. Compared with the target parameter estimation in nonlinear system, the Calman filter algorithm is not suitable for the nonlinear system, particle filter algorithm has high adaptability to the target estimation in nonlinear and non Gauss systems. In this paper, the particle filter is used to realize the real time estimation of battery capacity. Here we using iron manganate lithium battery as the research object£¬the capacity estimation and estimation methods of Li ion batteries are studied in depth.
¡¡¡¡In this paper, the hardware circuit system for the detection and estimation of the parameters of electric vehicle batteries based on stm32 as the core controller is designed. In this paper, we first introduce the design of each hardware module circuit, including voltage signal detection module, current signal detection module, power supply module and several communication modules. Secondly, this paper introduces and analyzes several models of power battery and the estimation method of battery, and emphatically introduces the principle and implementation steps of the particle filter algorithm of battery capacity estimation. Finally, the pulse discharge test and city road condition test of battery group were do in the laboratory environment, the test results show that the particle filter algorithm can quickly converge and has the estimation accuracy of the experimental requirements to the real capacity of the battery while the initial conditions of battery capacity is not accurate.
¡¡¡¡Key words£ºElectric Vehicle, Lithium Battery, Parameter Acquisition, Particle Filter, Capacity Estimation
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