Predictive Energy Management of Plug-in Hybrid Electric Vehicles by Real-time Optimization and Data-driven Calibration

Author(s):  
Ningyuan Guo ◽  
Xudong Zhang ◽  
Yuan Zou ◽  
Guangze Du ◽  
Chao Wang ◽  
...  
2021 ◽  
pp. 219-242
Author(s):  
D. Pritima ◽  
S. Sheeba Rani ◽  
P. Rajalakshmy ◽  
K. Vinoth Kumar ◽  
Sujatha Krishnamoorthy

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.


2020 ◽  
Vol 53 (2) ◽  
pp. 14224-14229
Author(s):  
Yongkeun Choi ◽  
Jacopo Guanetti ◽  
Scott Moura ◽  
Francesco Borrelli

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