A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

Panday, Aishwarya; Bansal, Hari Om

doi:10.1155/2014/160510

Cited by 188 publications

(114 citation statements)

References 139 publications

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“…A variety of strategies have been proposed and evaluated in many previous studies [4]. A detailed literature review on EMS for PHEVs is provided in this section.…”

Section: Ems For Phevsmentioning

confidence: 99%

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Development and Evaluation of an Evolutionary Algorithm-Based OnLine Energy Management System for Plug-In Hybrid Electric Vehicles

Boriboonsomsin

et al. 2017

IEEE Trans. Intell. Transport. Syst.

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Abstract-Plug-in hybrid electric vehicles (PHEVs) have been regarded as one of several promising countermeasures to transportation-related energy use and air quality issues. Compared with conventional hybrid electric vehicles, developing an energy management system (EMS) for PHEVs is more challenging due to their more complex powertrain. In this paper, we propose a generic framework of online EMS for PHEVs that is based on an evolutionary algorithm. It includes several control strategies for managing battery state-of-charge (SOC). Extensive simulation testing and evaluation using real-world traffic data indicates that the different SOC control strategies of the proposed online EMS all outperform the conventional control strategy. Out of all the SOC control strategies, the self-adaptive one is the most adaptive to real-time traffic conditions and the most robust to the uncertainties in recharging opportunity. A comparison to the existing models also employing short-term prediction shows that the proposed model can achieve the best fuel economy improvement but requiring less trip information.Index Terms-Plug-in hybrid electric vehicle, intelligent transportation system, energy management, evolutionary algorithm.

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“…A variety of strategies have been proposed and evaluated in many previous studies [4]. A detailed literature review on EMS for PHEVs is provided in this section.…”

Section: Ems For Phevsmentioning

confidence: 99%

“…Numerous efforts have been made in developing a variety of EMS for PHEVs [3], [4]. From the control perspective, existing EMS can be roughly classified as rule-based [5] and optimization-based [6].…”

mentioning

confidence: 99%

Development and Evaluation of an Evolutionary Algorithm-Based OnLine Energy Management System for Plug-In Hybrid Electric Vehicles

Boriboonsomsin

et al. 2017

IEEE Trans. Intell. Transport. Syst.

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show abstract

“…This strategy splits overall vehicle power requirement between FC and MC. Power ratio is considered as optimal when sum of fuel consumption of FC and equivalent fuel consumption of MC is minimal [19]- [20]. Vehicle parameters are shown in Table 2.…”

Section: Model and Configuration Of The Vehiclementioning

confidence: 99%

Optimization of Hybrid Vehicle Drivetrain with Genetic Algorithm using Matlab and Advisor

Biroš¹,

Karol²

2017

JESTR

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Advantages of hybrid vehicles over pure electric vehicles are obvious and well-known. The paper presents a simulation study of the optimization of hybrid propulsion drivetrain. A vehicle model was optimized in order to scale drivetrain components to achieve better fuel economy and lower greenhouse emissions. A set of ADVISOR data for vehicle was optimized by genetic algorithm in Matlab. Simulation results show significant fuel economy improvement.

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“…Different types of electric vehicles such as hybrid electric vehicles (HEVs) [13,14] and plug-in electric vehicles (PEVs) [15] also produce little emission of pollutants due to their energy saving ability [16]. Different ways of battery power management are evident in different types of electric vehicles.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach of Improving Battery Performance and Longevity of the Developed Electrically Assisted Triwheeler Vehicle by Implementing Torque Sensor Technology

Rashid

Rahman

Siddique

et al. 2017

International Journal of Vehicular Technology

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This paper presents a new approach to improving the battery performance and its longevity by the implementation of torque sensor pedal technology on the developed electric triwheeler vehicle (i.e., wheelchair). The paper has also discussed integration of the torque sensor technology with the overall electrical system of the vehicle. Incorporating the components of torque sensor technology reduces the human effort immensely by providing assistance from the battery bank to drive a hub motor while maneuvering the wheelchair using the torque sensor pedal. Field tests were carried out in three different stages, one with pedal, one with the throttle only, and with varying the load on the wheelchair, to distinguish the effect of load test on battery performance using the pedal. Results of the field tests reveal that the state of charge of batteries has been minimized using the pedal due to the contribution of the muscular energy of the user along with the battery energy to meet the total energy demand of the motor. Analyzing test results with the torque sensor pedal clarifies that the vehicle covers a longer distance, lessens power dissipation from the batteries, and reduces energy consumption from the batteries, which leads to improvement of the battery performance and its longevity ensuring sustainability of the electric vehicle.

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A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

Cited by 188 publications

References 139 publications

Development and Evaluation of an Evolutionary Algorithm-Based OnLine Energy Management System for Plug-In Hybrid Electric Vehicles

Development and Evaluation of an Evolutionary Algorithm-Based OnLine Energy Management System for Plug-In Hybrid Electric Vehicles

Optimization of Hybrid Vehicle Drivetrain with Genetic Algorithm using Matlab and Advisor

A Novel Approach of Improving Battery Performance and Longevity of the Developed Electrically Assisted Triwheeler Vehicle by Implementing Torque Sensor Technology

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