A fuel cell hybrid energy management method and system for a vehicle

Abstract

The present invention relates to a fuel cell hybrid power energy management method and system for a vehicle. The method updates the working condition table at intervals, and calculates the demand power transfer matrix generated based on the current updated working condition table data and is generated based on the current new working condition table. The Pearson correlation coefficient ρ between the demand power transfer probability matrix and the matrix generated based on the previous working condition table is used to determine whether to update the energy management strategy; when the absolute value of the Pearson correlation coefficient ρ is less than the reference threshold λ, the Q‑ The learning algorithm uses optimization iterations to calculate a new optimal energy management strategy to update the energy management strategy and apply it to the system; when the absolute value of ρ is greater than or equal to λ, the original energy management strategy is retained. The invention uses the Pearson correlation coefficient of the required power transfer probability matrix as a basis to update the energy management strategy when the working condition changes, thereby enhancing the real-time performance of the energy management strategy and improving the energy utilization rate.

Description

technical field [0001] The invention belongs to the technical field of energy management of a hybrid power supply system, and specifically refers to a fuel cell hybrid energy management method and system for a vehicle. Background technique [0002] Today's increasingly stringent carbon emission regulations have made electric vehicles a mainstream trend in the automotive industry. Fuel cell hybrid vehicles have the characteristics of zero emission, high efficiency, diversified fuel sources, and renewable energy, which has attracted widespread attention. For fuel cell hybrid electric vehicles, the key issue is to design an efficient and adaptive energy management strategy, so that fuel cells and lithium batteries can distribute power reasonably under various driving conditions. [0003] Previous studies have mainly focused on the optimization of energy management strategies for a given driving cycle, and these globally optimal management strategies exhibit good fuel economy f...

AI Technical Summary

Problems solved by technology

However, the application of offline methods in practice is still very limited due to the uncertainty of the driving conditions in which they are implemented.

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