scholarly journals Hierarchical control strategies for energy management of connected hybrid electric vehicles in urban roads

2016 ◽  
Vol 62 ◽  
pp. 70-86 ◽  
Author(s):  
Baisravan HomChaudhuri ◽  
Runing Lin ◽  
Pierluigi Pisu
Author(s):  
Runing Lin ◽  
Baisravan HomChaudhuri ◽  
Pierluigi Pisu

This paper presents a fuel efficient control strategy for a group of connected hybrid electric vehicles (HEVs) in urban road conditions. A hierarchical control architecture is proposed in this paper where the higher level controller is considered to be a part of the transportation infrastructure while the lower level controllers are considered to be present in every HEV. The higher level controller uses model predictive control strategy to evaluate the energy efficient velocity profiles for every vehicle for a given horizon. Each lower level controller then tracks its velocity profile (obtained from the higher level controller) in a fuel efficient fashion using equivalent consumption minimization strategy (ECMS). In this paper, the vehicles are modeled in Autonomie software and the simulation results provided in the paper shows the effectiveness of our proposed control architecture.


2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Aishwarya Panday ◽  
Hari Om Bansal

Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a ready reference for the researchers working in the area of energy optimization of hybrid vehicles.


Author(s):  
Pierluigi Pisu ◽  
Giorgio Rizzoni ◽  
Cristian Musardo ◽  
Benedetto Staccia

Hybrid Electric Vehicles (HEVs) improvements in fuel economy and emissions strongly depend on the energy management strategy. Big obstacles to the control design are the model complexity and the necessity of “a priori” knowledge of torque and velocity profiles for optimal torque split. This paper presents and compares four different energy management approaches for the control of a parallel hybrid electric sport-utility-vehicle.


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.


Author(s):  
Carlos Villarreal-Hernandez ◽  
Javier Loranca-Coutino ◽  
Omar F. Ruiz-Martinez ◽  
Jonathan C. Mayo-Maldonado ◽  
Jesus E. Valdez-Resendiz ◽  
...  

2014 ◽  
Vol 15 (3) ◽  
pp. 1145-1154 ◽  
Author(s):  
Viktor Larsson ◽  
Lars Johannesson Mardh ◽  
Bo Egardt ◽  
Sten Karlsson

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