| Development of Multi-source Information Fusion Based Novel Energy Management Strategy for 4WD PHEV |
| Chao Ma, Dechao Yan, Tong Sun, Kun Yang, Di Tan |
| School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China |
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Received: July 10, 2023; Revised: May 13, 2024 Accepted: July 23, 2024. Published online: October 1, 2024. |
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| ABSTRACT |
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In this paper, the multi-source information fusion (MIF) of human-vehicle–road-based energy management strategy (EMS) is developed for a four-wheel drive plug-in hybrid electric vehicle (4WD PHEV). First, the characteristics of 4WD PHEV configuration are analyzed. Second, a fuzzy inference method is used for driving intention recognition. Actual driving experiments are performed through the developed virtual simulated driving environment to obtain the inter-vehicle motion characteristics. Based on the MIF of driving intention, inter-vehicle motion characteristics and historical velocity, an online GA-BP velocity prediction method is developed. The online model predictive control framework is then proposed to achieve minimal fuel consumption, which combines the mathematical model of MIF based GA-BP and Dynamic Programming (DP) algorithm. The DP algorithm is selected as the solver for rolling optimization in the prediction time domain. The MIF based EMS is established with real time application capability. Finally, the simulation results show that the MIF-based strategy improves the vehicle economy by 25.11% compared with the rule based strategy. |
| Key Words:
4WD PHEV · Multi-source information fusion · Velocity prediction · Driving intention · Model predictive control · Dynamic programming |
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Corresponding Author.
Kun Yang , Email. 
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