Modeling and control strategy development for fuel cell hybrid vehicles

Ning, Qian; Xuan, Dongji; Kim, Y.

doi:10.1007/s12239-010-0029-x

Cited by 23 publications

(15 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wu et al (2012) presented a fuzzy energy management strategy (EMS) based on driving cycle recognition to improve the fuel economy of a parallel hybrid electric vehicle by considering the effect of the driving cycle on the EMS. Ning et al (2010) constructed a comprehensive simulation model for the fuel cell hybrid vehicle (FCHV) power train in parallel with a power control strategy that uses a logic threshold approach implemented with a hybrid control unit. The proposed optimal configuration model has six possible operating modes and power flows between each subsystem according to the particular conditions identified by the system operation.…”

Section: Introductionmentioning

confidence: 99%

Development a new power management strategy for power split hybrid electric vehicles

Montazeri-Gh

Mahmoodi-k

2015

Transportation Research Part D: Transport and Environment

104

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Development a new power management strategy for power split hybrid electric vehicles

Montazeri-Gh

Mahmoodi-k

2015

Transportation Research Part D: Transport and Environment

104

View full text Add to dashboard Cite

“…In the case of use of fuel cell (FC), as the primary source of energy, the “series” hybrid configuration must be adopted. In this configuration, the sum of the power from the primary converter and a rechargeable energy atorage system (RESS) is electrical and the power is transferred to the wheel only by an electric machine (EM) 13, 14. In this work, the primary energy source is a PEMFC stack, while the RESS is a Lithium‐ion battery.…”

Section: Introductionmentioning

confidence: 99%

Strategies for Dimensioning Two‐Wheeled Fuel Cell Hybrid Electric Vehicles Using Numerical Analysis Software

et al. 2016

View full text Add to dashboard Cite

Owing to the limitation of fossil fuels and high consumption and pollution for transportation, the vehicle industry is looking for other sources of energy. A fuel cell hybrid electric vehicle (FCHEV) could be a suitable solution considering the state of the art of main components. This paper presents the simulation of powertrains for FCHEVs in order to dimension the fuel cell (FC) as primary source of energy and to investigate the power flows during both motoring and recuperative braking. For this purpose a Matlab/Simulink® model has been built up which can be used for a wide range of applications. The results of simulation show which is the best powertrain configuration for two‐wheeled vehicles in three different cases: a bike in which the traction force is provided by both electric motor and the pedaling of the cyclist, a bike in which the traction force is provided only by an electric motor without pedaling and a motorcycle for 2 passengers. Specifically, the consumption, the state of charge (SOC) of battery and the amount of energy generated by each source of energy have been monitored. The model validation was done by comparison between the obtained results and scientific articles in the literature.

show abstract

“…WU et al [13] presented a fuzzy energy management strategy (EMS) based on driving cycle recognition to improve the fuel economy of a parallel hybrid electric vehicle by considering the effect of the driving cycle on the EMS. NING et al [14] constructed a comprehensive simulation model for the fuel cell hybrid vehicle (FCHV) power train in parallel with a power control strategy that uses a logic threshold approach implemented with a hybrid control unit. The proposed optimal configuration model has six possible operating modes and power flows between subsystems according to the particular conditions identified by the system operation.…”

Section: Introductionmentioning

confidence: 99%

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Montazeri-Gh

Mahmoodi-k

2015

J. Cent. South Univ.

View full text Add to dashboard Cite

Due to soaring fuel prices and environmental concerns, hybrid electric vehicle (HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.

show abstract

Modeling and control strategy development for fuel cell hybrid vehicles

Cited by 23 publications

References 13 publications

Development a new power management strategy for power split hybrid electric vehicles

Development a new power management strategy for power split hybrid electric vehicles

Strategies for Dimensioning Two‐Wheeled Fuel Cell Hybrid Electric Vehicles Using Numerical Analysis Software

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Contact Info

Product

Resources

About