Abstract
To address the issue of poor fuel economy induced by the inaccurate vehicle speed prediction in the predictive energy management strategy of plug-in hybrid electric vehicle, a vehicle speed combination prediction model based on optimizing variational mode decomposition and long-term and short-term neural networks with the sparrow-search algorithm was proposed. Under the model predictive control framework, the prediction model was used to predict the future vehicle speed, and the global optimization problem was transformed into the optimal distribution problem of power source torque in the prediction time domain. With the minimum fuel consumption as the optimal goal, the dynamic programming algorithm was used to solve the optimization problem in the prediction time domain. Compared with LSTM prediction model, the proposed combined prediction model improved the prediction accuracy by 59.57% according to the simulation, and the predictive energy management strategy reduced fuel consumption by 4.58%. Compared with the rule-based strategy, it reduced fuel consumption by 15.1%.
Key words
PHEV /
predictive control /
energy management /
vehicle speed prediction
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WEI Liqing，QIANG Yongjun.
PHEV Predictive Energy Management Strategy Based on Vehicle Speed Prediction[J]. Vehicle Engine. 2024, 0(2): 83 https://doi.org/10.3969/j.issn.1001-2222.2024.02.012
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