EV Lithium-ion Battery Monitoring And Management System Design And SOC Estimates

The rapid development of automobile industry has made environmental pollution and energy shortage worse. The traditional car consumes a huge amount of energy and discharges a large amount of pollutants. The combustion engine uses fossil fuels with low efficiency of the energy conversion. It is these conditions that make electric vehicles become hot again after the ups and downs. Many governments all put forward plans and support measures to promote the development of electric vehicles. Research institutions and enterprise group all actively involve in, and make a lot of results. As the core power components of the electric vehicle, the battery has a significant impact on the using performance of the vehicle. Among many batteries, lithium-ion batteries stand out because of its excellent overall performance and gain widespread attention and rapid development. The overall study of electric vehicle battery power system can be divided into mechanical structure design of the battery pack itself and the research of the battery management system.In this paper, a battery monitoring&management system was designed based on the needs of the project. The hardware of the system included two parts:acquisition and control modules. he acquisition module measures the current and the temperature of the cells. On the one hand, the control module monitored the real-time voltage, current, insulation resistance etc. of the total package. On the other hand, it received the messages of the cell from acquisition module through the CAN bus, and managed the charging and discharging, temperature, balancing and other things of the power battery after processing the data. And meanwhile, it communicated with the upper-position computer through the serial port.The upper-position computer software of the system had the following functions:1. to set the limits on the current, voltage, temperature and other running parameters of the system;2.to show the battery working with flash;3. to communicate with lower-position computer through the serial port;4. to process the data from lower-position computer, to show and storage it, and monitor the system state;5. to choose different methods to estimate and display SOC using the measured data;6. to select the different equivalent circuit model, and set the appropriate parameters for battery simulation.Because of SOC estimation problem, this paper selected the Kalman filtering for SOC estimation, and the equivalent circuit model was Thevenin model. When fitting the OCV-SOC curve, this article divided the plateau phase of the curve into two parts, fit them separately using Matlab toolbox and verified the improvement by comparing the fitting results.To identify the dynamic parameters of the battery, this paper did the discharge experiment with a constant load. After getting the load voltage, this paper calculated the value of every parameter gradually according to the zero-state response of the circuit model. And a Simulink model with these parameters was set up to verify the effect.The results showed that this attempt is successful. Finally, by using the data obtained, the simulation under the HPPC condition was made to verify the effectiveness of the Kalman filtering algorithm.