A hybrid vehicle energy optimization method based on battery life decay pattern recognition

A battery life, hybrid vehicle technology, applied in electric vehicles, hybrid vehicles, motor vehicles, etc., can solve the problem of not having universal working conditions, unable to represent the battery life attenuation law, unable to achieve battery performance and vehicle economy On-line real-time optimal control and other problems

CN110775043BActive Publication Date: 2020-09-29JILIN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2020-09-29

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Abstract

The invention discloses a hybrid electric vehicle energy optimization method based on battery life attenuation mode identification. The control method comprises the following steps that energy management optimization control strategies under a China passenger vehicle working condition, a new European driving cycle (NEDC) working condition and a highway fuel economy test (HWFET) working condition are generated respectively for a hybrid electric vehicle, and the sums of the fuel consumption costs and the battery life attenuation costs of stages are taken as an optimized objective function; and the battery life attenuation mode under each working condition is classified based on the result of solution based on a discrete dynamic programming algorithm, finally a battery life attenuation mode is identified based on the neural network, and a control strategy which can be applied to a real vehicle online in real time under the corresponding mode is established. According to the hybrid electric vehicle energy optimization method based on the battery life attenuation mode identification, based on the working condition dimension, the battery life attenuation rule is extracted, the battery life attenuation mode is identified, the battery life attenuation degree is effectively relieved, the fuel economy is guaranteed, and the accuracy of a system on the battery life prediction under an actual driving condition and the adaptability of the system to the actual driving condition are improved.
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Description

technical field

[0001] The invention belongs to the technical field of hybrid electric vehicle energy management, and more precisely, the invention relates to an energy optimization method of a hybrid electric vehicle based on identification of battery life attenuation patterns. Background technique

[0002] There are multiple power sources in hybrid electric vehicles, and it is necessary to coordinate the working status of each power source to meet the power demand of the vehicle, and then give full play to its energy-saving advantages. The performance of the power battery directly affects the performance of the drive motor, thereby affecting the fuel economy and emission performance of the vehicle, which is the key to the performance of the vehicle. Studies have shown that fuel economy and battery life attenuation are mutually influential. The current research on energy optimization management strategies mainly achieves the best fuel economy under specific working conditio...

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Embodiment Construction

[0061] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0062] refer to figure 1 , the present invention discloses an energy optimization method for hybrid vehicles based on battery life attenuation pattern recognition. Firstly, the energy management optimization control strategies for Chinese passenger car operating conditions, NEDC operating conditions and HWFET operating conditions are respectively formulated. The sum of fuel consumption cost and battery life attenuation cost is used as the optimization objective function, and the discrete dynamic programming algorithm is used to solve it; then 13 characteristic parameters are selected, covering the characteristics of working conditions and battery life characteristics, and the global optimization results under each working condition are calculated according to The recognition cycle ΔT is equally divided to obtain the corresponding working condition block, and then the...