Method of dynamically correcting residual electric quantity based on cell characteristic

Abstract

A method of dynamically correcting a residual electric quantity based on a cell characteristic is disclosed. A technical main point of the invention is characterized in that a power cell with a current acquisition unit, a temperature acquisition unit and a high voltage acquisition unit and a cell characteristic data memory cell are used; based on disadvantages and limitation of an existing residual electric quantity analysis method, a residual electric quantity method which is suitable for engineering is provided. In the method, an ampere-hour integral method and an electromotive force method are combined through a weighting factor. According to the cell characteristic, a set of dynamic adjusting weighting factor strategy is provided. By using the method, a disadvantage that the ampere-hour integral method is easy to achieve divergence is effectively overcome; and precision of residual electric quantity estimation is increased. Through a real vehicle, validity, practicality and feasibility of the method are verified.

Description

technical field [0001] The invention relates to the technical field related to the remaining power of a power battery, in particular to a method for dynamically correcting the remaining power based on battery characteristics. The invention is suitable for pure electric vehicles and hybrid electric vehicles that need to use power batteries. Keywords of the present invention: SOC estimation, ampere-hour integration method, battery management system, battery characteristics. Background technique [0002] With the continuous development of society, environmental issues have received more and more attention, and vehicle exhaust emissions have become one of the main factors affecting the environment. In addition, considering the non-renewable nature of oil and the continuous increase in car ownership, therefore Finding a clean alternative to petroleum energy is the only way to solve the above problems, and electric vehicles arise at the historic moment. [0003] Battery manageme...

AI Technical Summary

Problems solved by technology

The simple ampere-hour integration method is actually an open-loop prediction method. Its advantage is that it is simple to implement. Its disadvantage is that due to the influence of sensor sampling accuracy and sampling period, it will produce a large cumulative estimation error. If this method is used for a long time SOC calculation, without correction, the cumulative error will reach more than 50%, so the ampere-hour integration method needs to be used in combination with other methods; and the open circuit voltage method needs to be static for the battery in advance, so this method is only applicable to battery packs The experimental measurement is not suitable for the real-time SOC calculation requirements of electric vehicles; both the electromotive force method and the Kalman (Kalman filter) filter method rely on an accurate battery model, and the accuracy of the model directly affects the calculation of SOC, but because the power battery itself is For a nonlinear complex time-varying system, it is almost impossible to accurately estimate its model, so the simple electromotive force method and Kalman filtering method are not feasible in engineering; in addition, the computational complexity of Kalman filtering is also a problem that needs to be considered; based on the above analysis, it is necessary for us to propose a reasonable and accurate SOC calculation method suitable for engineering

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