Method for estimating SOH of battery pack

A battery pack and a priori estimation technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of inability to measure in real time online and high cost

Inactive Publication Date: 2016-09-28
OPTIMUM BATTERY CO LTD
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Problems solved by technology

[0004] In view of the defects of the prior art, the purpose of the present invention is to provide a method for estimating the SOH of a battery p

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  • Method for estimating SOH of battery pack
  • Method for estimating SOH of battery pack

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[0025] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0026] The traditional estimation methods of State-of-Health (SOH) of battery pack mainly include: definition method, resistance conversion method, capacity decay method, chemical analysis method, partial discharge method, impedance analysis method and AC impedance analysis method, etc. These methods are mainly based on the battery cycle charge and discharge test, and analyze the change of battery characteristics to estimate the SOH of the battery. The disadvantages are waste, long test period, and inability to measure online in real time. They are not suitable for the use requirements of electric v...

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Abstract

The invention discloses a method for estimating SOH of a battery pack. The method is characterized by, estimating the SOH of the battery pack through double adaptive extended Kalman filtering algorithm; estimating battery Ohm inner resistance and battery charge state online through two independent Kalman filters; and reflecting the SOH of the battery through change of the battery Ohm inner resistance. In the aspect of parameter setting, an original kalman filtering algorithm setting mode is changed into a parameter-adaptive change mode, so that algorithm convergence is better; and the whole algorithm is less influenced by parameter initial value setting, and the algorithm is easy to transplant and is relatively stable in the operation process. The adaptive extended Kalman filtering algorithm is actually a kind of recursive linear minimum variance estimation; and through algorithm real-time observation value and the estimated value at the last moment, the SOH is estimated in real time, and thus the state of health of the battery can be reflected in time. The method is suitable for various occasions of the battery; and compared with other method, the double adaptive extended Kalman filtering algorithm can reflect the SOH of the battery pack dynamically, and the method is more suitable for the severe-current-fluctuation electromobile application environment.

Description

technical field [0001] The invention belongs to the technical field of battery management, and more specifically relates to a method for estimating the SOH of a battery pack. Background technique [0002] The energy crisis and environmental pollution have sounded the alarm to human beings, so how to replace traditional fuel vehicles has become a topic of debate for a long time. At present, electric vehicles using power lithium-ion battery packs as a power source are highly concerned and favored by people, and have become a research hotspot for new energy vehicles. In addition to the research on the power lithium-ion battery itself, the research on the battery management system is also in progress. Among them, the battery management system accurately estimates the health status of the lithium-ion battery. The biggest defect of the management system directly affects the practicability, economy, safety and other aspects of the lithium-ion battery pack. [0003] The traditiona...

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Application Information

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IPC IPC(8): G01R31/36
CPCG01R31/367G01R31/3842G01R31/389G01R31/396
Inventor 张鲁宁
Owner OPTIMUM BATTERY CO LTD
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