Advanced Power Management and Control for Hybrid Electric Vehicles: A Survey

Jiang, Jielin; Jiang, Qinting; Chen, Jinhui; Zhou, Xiaoping; Zhu, Shufeng; Chen, Tianyu

doi:10.1155/2021/6652038

Cited by 5 publications

(4 citation statements)

References 79 publications

(88 reference statements)

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“…In the first steering, ICE torque is transmission directly to the wheels, in the second steering, the torque produced by EM is transmission to the wheels, and in the third steering, the torque produced by ICE is transmission to the electric motor and the electric motor operates as a generator. Figure 5 shows the torque movements between ICE, EM and wheels [37][38][39].…”

Section: Parallel Hybrid Vehicle Operating Modesmentioning

confidence: 99%

Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy

Kocakulak¹,

Solmaz²,

Şahin³

2023

Politeknik Dergisi

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In this study, a model of a pre-transmission parallel hybrid vehicle was created in MATLAB/Simulink environment. A torque control strategy has been developed for the hybrid vehicle on the created model. The hybrid vehicle's torque control is provided by fuzzy logic and conventional rule-based control strategies. The control strategies of the hybrid vehicle have been developed based on four input parameters: accelerator and brake pedal position, battery state of charge and the operating mode of the electric motor. The regenerative braking system of the pre-transmission parallel hybrid vehicle has been provided with a fuzzy logic control strategy in both vehicle structures. In the fuzzy logic torque split controller, a control algorithm has been created in which the safety, performance and fuel consumption values of the vehicle meet at the optimum point. Under different driving cycle conditions, the effects of control strategies on engine operating points have been examined and average fuel consumption values have been obtained. In the control of the parallel hybrid vehicle with fuzzy logic method, it has been obtained that it provides 12.87%, 6.62%, 2.27% and 6.23% fuel savings under FTP-75, NEDC, EUDC and ECE-15 driving cycle conditions, respectively. It has been observed that the vehicle cannot provide sufficient performance in US06 driving cycle conditions with the use of conventional rule-based control strategy.

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Section: Parallel Hybrid Vehicle Operating Modesmentioning

confidence: 99%

Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy

Kocakulak¹,

Solmaz²,

Şahin³

2023

Politeknik Dergisi

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“…A huge amount of information causes a heavy computation load or perhaps makes computation impossible. As a result, without realistic optimisation for computational load, several power management methodologies (such as DP) cannot be employed for the power management of HEVs [188].…”

Section: Computational Loadmentioning

confidence: 99%

Energy management strategies of hybrid electric vehicles: A comparative review

Azim Mohseni,

Bayati,

Ebel

2023

IET Smart Grid

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With increasing environmental problems, including air pollution, rising greenhouse gases and global warming, the need to use clean energy resources seems essential. Therefore, the usage of clean and renewable energy sources is suggested as a suitable solution to overcome the mentioned concerns. The transportation section contributes to a huge percentage of energy consumption. Hybrid electric vehicles (HEVs), by combining several energy resources, are considered as a crucial solution to decrease fossil fuel consumption and improve the environmental challenges. The existence of an alternative energy resource and the internal combustion engine together provides optimal power distribution among them to maximise power usage and minimise fuel consumption. Energy management strategy (EMS) is an essential challenge in HEV's design procedure to deal with the power distribution in multiple power source systems to improve the performance of the HEVs. A review of various EMSs for HEVs, followed by an analysis of each type, including its benefits and drawbacks, is presented by the authors. In addition to this, the major challenges in EMSs for HEVs are described and a comprehensive review is presented for strategies addressing these issues.

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“…Due to the importance of developing the industry of electric cars, numerous researchers interested in providing models that tackled different visions of facing problems. The authors of [11] presented a deep review study on the provided energy management methods for hybrid electric vehicles. Moreover, different optimization algorithms have been studied to point out the solutions for the appeared issues.…”

Section: Related Workmentioning

confidence: 99%

Management System of Smart Electric Vehicles Using Software Engineering Model

Croock

Mahmood

2022

Int. j. electr. comput. eng. syst. (Online)

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In this paper, a management system for smart electric vehicle is introduced using software engineering models and installed Sensor Network (SN). Two software engineering models are proposed to construct information exchange and available resource management algorithms, in which the required performance of vehicles is obtained. The resource management algorithm adopts the LeNet-5 deep-learning model in choosing the best driving mode. The datset is achieved from the simulated sensor Network (SN). The results show the satisfied performance of the electric cars in terms of information exchange and resource management. The MQTT broker server is employed for monitoring the information exchange algorithm, where the delay time is less than 1 sec for transmitting 1000 message. The proposed system saves power by 1-8 Kwh and a storage capacity by 9-95 MB for driving 100Km.

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Advanced Power Management and Control for Hybrid Electric Vehicles: A Survey

Cited by 5 publications

References 79 publications

Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy

Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy

Energy management strategies of hybrid electric vehicles: A comparative review

Management System of Smart Electric Vehicles Using Software Engineering Model

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