Global Optimisation in the power management of a Fuel Cell Hybrid Vehicle (FCHV)

Bernard, J.; Delprat, Sébastien; Buechi, Felix N.; Guerra, Thierry Marie

doi:10.1109/vppc.2006.364289

Cited by 44 publications

(15 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The result of this analysis can be used to compare the performance of the energy management strategies that command the FCS operation [28]. In some works, e.g., [23], [29], and [30], this minimum value is determined through the use of the dynamic programming (DP) technique, which is a procedure that allows calculating a global optimal operation of the system for a given load profile by evaluating all possible control sequences in a systematic way [29] or through the use of the optimal control theory [31]. However, a disadvantage of the DP technique is the relatively long computation time due to the large required grid density.…”

Section: Computation Of the Optimal Hydrogen Consumption In The Fmentioning

confidence: 99%

Design and Analysis of Fuel-Cell Hybrid Systems Oriented to Automotive Applications

Feroldi

Serra

Riera

2009

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Abstract-Hybridization with high specific energy-storage devices such as supercapacitors (SCs) has important advantages in fuel-cell (FC)-based systems. This paper presents an approach for the design and analysis of FC hybrid systems (FCHSs) oriented to automotive applications. The FCHS is considered to be the most attractive long-term option for propulsion of passenger cars. The design stage includes the determination of the electrical topology and the determination of the hybridization degree (HD) according to drivability conditions. With the selected design, the optimal hydrogen consumption for different driving cycles and the energy flows in the hybrid vehicle are analyzed. The entire study is performed with a detailed model of the FCHS in the Advanced Vehicle Simulator (ADVISOR): the determination of the HD according to drivability requirements, the analysis of the energy flows, and the computation of the optimal hydrogen consumption. The results show that hybridization allows a significant improvement in the hydrogen economy through the recovered energy from breaking. At the same time, the results suggest a conflict between a design according to drivability conditions and a design for the highest efficiency. The conclusion is that hybridization with SCs in FC-based vehicles is a meaningful procedure that enhances performance.

show abstract

Section: Computation Of the Optimal Hydrogen Consumption In The Fmentioning

confidence: 99%

Design and Analysis of Fuel-Cell Hybrid Systems Oriented to Automotive Applications

Feroldi

Serra

Riera

2009

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…Gurkaynak et al [6] propose a control strategy for HEV based on the equivalent consumption minimization strategy (ECMS) and they use a neural network to recognize driving cycles to help reduce the algorithm's sensitivity to variations in these cycles. Bernard et al [7] propose a global optimization algorithm based on optimal control theory to manage the power flow between the fuel cell and the storage system under several constrains.…”

Section: Introductionmentioning

confidence: 99%

Neural Network Technique for Hybrid Electric Vehicle Optimization

2017

View full text Add to dashboard Cite

Large inaccuracies exist in the car speed forecast due to the driver actions, the vehicle, and r2016oad conditions, which are not known a priori. Hence, real time scheduling using optimization methods is not feasible in general. So, an energy management system based on artificial neural network looking one step ahead is presented to minimize the cost of hydrogen and battery degradation. The optimum results of dynamic programming are used to provide a data set used to train an artificial neural network offline which would help solve the problem of real-time implementation. The inputs of the artificial neural network are fuel cell power, the battery state of charge, and the demand forecast; whereas, the output is the fuel cell power. The results obtained by the artificial neural network are compared to those obtained by dynamic programming and found to be very close. The artificial neural network is trained using the standard Urban Dynamometer Driving Schedule, and is able to provide charge sustaining and charge depletion operations. It is also tested on ten percent faster and ten percent slower variations of the same cycle, as well as on the Highway Fuel Economy Test Cycle and New European Driving cycle. The tests show a very good generalization capability of the developed artificial neural network on the different drive cycles.

show abstract

“…Therefore, power management strategies for hybrid vehicles have become a popular research topic. Several types of power management strategies have been developed so far, such as optimal control strategies based on optimal control theory (Bernard et al, 2006;Bernard et al, 2010;Kim, and Peng, 2007), equivalent consumption minimization strategy (ECMS) (Xu et al, 2009), and rule-based power management strategies (Ehsani et al, 2010). The optimal control theory here includes Dynamic Programming (DP) and Pontryagin's Minimum Principle (PMP).…”

Section: Introductionmentioning

confidence: 99%

Numerical comparison of ECMS and PMP-based optimal control strategy in hybrid vehicles

Zheng

et al. 2014

Int.J Automot. Technol.

View full text Add to dashboard Cite

During the last decade, the equivalent consumption minimization strategy (ECMS) and the Pontryagin's Minimum Principle (PMP)-based optimal control strategy have been developed for power management of hybrid vehicles, and it has been noticed that there are some similarities between the two strategies. Establishing their exact relationship and distinguishing their fundamental differences have become necessary for further development in the field of power management strategy. The two strategies are numerically compared and their relationship is established in this research. The two strategies are applied to a fuel cell hybrid vehicle (FCHV) in a computer simulation environment and the simulation results of the two strategies are also compared. It is concluded that the numerical comparison result depends on the opencircuit-voltage (OCV) of the battery model. As a result, the ECMS and the PMP-based optimal control strategy can numerically have the same solutions for non-plug-in hybrid vehicles by adjusting two parameters. Differences between the two strategies are also discussed and the superiority of the PMP-based optimal control strategy is emphasized.

show abstract

Global Optimisation in the power management of a Fuel Cell Hybrid Vehicle (FCHV)

Cited by 44 publications

References 5 publications

Design and Analysis of Fuel-Cell Hybrid Systems Oriented to Automotive Applications

Design and Analysis of Fuel-Cell Hybrid Systems Oriented to Automotive Applications

Neural Network Technique for Hybrid Electric Vehicle Optimization

Numerical comparison of ECMS and PMP-based optimal control strategy in hybrid vehicles

Contact Info

Product

Resources

About