Online battery SOC (State of Charge) evaluation method based on charging voltage curve fused with Kalman filtering

Abstract

The invention discloses an online battery SOC evaluation method based on charging voltage curve fused with Kalman filtering. The method comprises phases of voltage curve characteristic analysis, battery terminal voltage solution in the discharging phase on the basis of a battery charging voltage curve, and evaluation of the battery SOC based on the charging voltage curve fused with Kalman filtering. In the first phase, a charging voltage and battery charging capacity relational curve under different aging states is obtained by actual measurement of the battery charging process, the battery capacity is normalized, and the curve is translated vertically to obtain an overlapped charging voltage and SOC relational curve after battery aging. In the second phase, a solution expression of the battery terminal voltage in the discharging phase is obtained from voltage expressions in the charging and discharging processes, and noise is introduced to analyze the influential factors and result ofvoltage. In the third phase, a battery terminal voltage measurement equation in a traditional Kalman filtering algorithm is replaced by the battery terminal voltage expression, so that the charging voltage curve is fused with Kalman filtering to evaluate the battery SOC.

Description

technical field [0001] The invention belongs to the technical field of electric vehicles, and in particular relates to a method for estimating state parameters of a power battery of an electric vehicle. Background technique [0002] Accurately estimating the battery state of charge (State of Charge, SOC) provides a reference for battery life estimation and safety assessment, which is conducive to improving the overall performance of the battery management system and ensuring the cruising range of electric vehicles. [0003] At present, the battery SOC is mostly estimated by the battery open circuit voltage method or the ampere-hour integration method. The typical algorithm is the Kalman filter algorithm. On the basis of the extended Kalman filter algorithm used to solve the battery SOC, the state equation of the battery model parameters is added. , by identifying the model parameters online, the battery SOC can be estimated more accurately. These estimation methods focus on...

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Problems solved by technology

According to the relationship curve between the battery terminal voltage and the charging power during the charging process of the battery, the researchers proposed to use the characteristics of the curve changing with the aging of the battery to perform translation correction to obtain the rated capacity value of the aging battery. However, how to use the charging voltage curve to eliminate battery management? The measurement error in the system, and then its application to the battery SOC online estimation still needs to be further studied

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