Power Flow in Hybrid Electric Vehicles and Battery Electric Vehicles

2021 ◽  
pp. 99-118
Author(s):  
Madhu S. ◽  
Ashwini A. ◽  
Karanam Vasudha
2004 ◽  
Vol 37 (22) ◽  
pp. 481-488
Author(s):  
Lucio Ippolito ◽  
Vincenzo Loia ◽  
Pierluigi Siano

2020 ◽  
Vol 10 (23) ◽  
pp. 8744
Author(s):  
Juan P. Torreglosa ◽  
Pablo Garcia-Triviño ◽  
David Vera ◽  
Diego A. López-García

The hybridization of vehicles is a viable step toward overcoming the challenge of the reduction of emissions related to road transport all over the world. To take advantage of the emission reduction potential of hybrid electric vehicles (HEVs), the appropriate design of their energy management systems (EMSs) to control the power flow between the engine and the battery is essential. This work presents a systematic literature review (SLR) of the more recent works that developed EMSs for HEVs. The review is carried out subject to the following idea: although the development of novel EMSs that seek the optimum performance of HEVs is booming, in the real world, HEVs continue to rely on well-known rule-based (RB) strategies. The contribution of this work is to present a quantitative comparison of the works selected. Since several studies do not provide results of their models against commercial RB strategies, it is proposed, as another contribution, to complete their results using simulations. From these results, it is concluded that the improvement of the analyzed EMSs ranges roughly between 5% and 10% with regard to commercial RB EMSs; in comparison to the optimum, the analyzed EMSs are nearer to the optimum than commercial RB EMSs.


Author(s):  
Guillermo Becerra ◽  
Jose´ Luis Mendoza-Soto ◽  
Luis Alvarez-Icaza

In this paper a new strategy for controlling the power flow in hybrid electric vehicles is described. The strategy focuses in the planetary gear system where kinematic and dynamic constraints must be satisfied. The aim is to satisfy driver demands and to reduce fuel consumption. The resultant power flow control is continuous and uses the internal combustion engine with the maximum possible efficiency. The strategy is not optimal, although it is inspired by the solution to most optimization problems. The main advantages are that the computational cost is low, when compared to optimization based approaches, and that it is easy to tune. The strategy is tested with simulations using a mathematical model of a power train of a hybrid diesel-electric bus subjected to the power demands of representative urban area driving cycles. Simulation results indicate that the strategy achieves small speed tracking errors and attains good fuel consumption reduction levels.


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