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Kumar BA, Jyothi B, Singh AR, Bajaj M, Rathore RS, Tuka MB. Hybrid genetic algorithm-simulated annealing based electric vehicle charging station placement for optimizing distribution network resilience. Sci Rep 2024; 14:7637. [PMID: 38561394 PMCID: PMC10984951 DOI: 10.1038/s41598-024-58024-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 03/25/2024] [Indexed: 04/04/2024] Open
Abstract
Rapid placement of electric vehicle charging stations (EVCSs) is essential for the transportation industry in response to the growing electric vehicle (EV) fleet. The widespread usage of EVs is an essential strategy for reducing greenhouse gas emissions from traditional vehicles. The focus of this study is the challenge of smoothly integrating Plug-in EV Charging Stations (PEVCS) into distribution networks, especially when distributed photovoltaic (PV) systems are involved. A hybrid Genetic Algorithm and Simulated Annealing method (GA-SAA) are used in the research to strategically find the optimal locations for PEVCS in order to overcome this integration difficulty. This paper investigates PV system situations, presenting the problem as a multicriteria task with two primary objectives: reducing power losses and maintaining acceptable voltage levels. By optimizing the placement of EVCS and balancing their integration with distributed generation, this approach enhances the sustainability and reliability of distribution networks.
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Affiliation(s)
- Boya Anil Kumar
- Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, India
| | - B Jyothi
- Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, India
| | - Arvind R Singh
- Department of Electrical Engineering, School of Physics and Electronic Engineering, Hanjiang Normal University, Shiyan, 442000, Hubei, People's Republic of China
| | - Mohit Bajaj
- Department of Electrical Engineering, Graphic Era (Deemed to Be University), Dehradun, 248002, India.
- Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
- Graphic Era Hill University, Dehradun, 248002, India.
- Applied Science Research Center, Applied Science Private University, Amman, 11937, Jordan.
| | | | - Milkias Berhanu Tuka
- Department of Electrical and Computer Engineering, College of Engineering, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.
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Oubelaid A, Kakouche K, Belkhier Y, Khosravi N, Taib N, Rekioua T, Bajaj M, Rekioua D, Tuka MB. New coordinated drive mode switching strategy for distributed drive electric vehicles with energy storage system. Sci Rep 2024; 14:6448. [PMID: 38499574 PMCID: PMC10948774 DOI: 10.1038/s41598-024-56209-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 03/04/2024] [Indexed: 03/20/2024] Open
Abstract
High performance and comfort are key features recommended in hybrid electric vehicle (HEV) design. In this paper, a new coordination strategy is proposed to solve the issue of undesired torque jerks and large power ripples noticed respectively during drive mode commutations and power sources switching. The proposed coordinated switching strategy uses stair-based transition function to perform drive mode commutations and power source switching's within defined transition periods fitting the transient dynamics of power sources and traction machines. The proposed technique is applied on a battery/ supercapacitor electric vehicle whose traction is ensured by two permanent magnet synchronous machines controlled using direct torque control and linked to HEV front and rear wheels. Simulation results highlight that the proposed coordinated switching strategy has a noteworthy positive impact on enhancing HEV transient performance as DC bus fluctuations were reduced to a narrow band of 6 V and transient torque ripples were almost suppressed.
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Affiliation(s)
- Adel Oubelaid
- Faculté de Technologie, Laboratoire de Technologie Industrielle et de l'Information, Université de Bejaia, Targa ouzemour, 06000, Bejaia, Algeria
| | - Khoudir Kakouche
- Faculté de Technologie, Laboratoire de Technologie Industrielle et de l'Information, Université de Bejaia, Targa ouzemour, 06000, Bejaia, Algeria
| | - Youcef Belkhier
- Institut de Recherche de l'Ecole Navale (EA 3634, IRENav), French Naval Academy, 29240, Brest, France
| | - Nima Khosravi
- Centre of Research Impact and Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India
| | - Nabil Taib
- Faculté de Technologie, Laboratoire de Technologie Industrielle et de l'Information, Université de Bejaia, Targa ouzemour, 06000, Bejaia, Algeria
| | - Toufik Rekioua
- Faculté de Technologie, Laboratoire de Technologie Industrielle et de l'Information, Université de Bejaia, Targa ouzemour, 06000, Bejaia, Algeria
| | - Mohit Bajaj
- Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, India.
- Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
- Graphic Era Hill University, Dehradun, 248002, India.
- Applied Science Research Center, Applied Science Private University, Amman, 11937, Jordan.
| | - Djamila Rekioua
- Faculté de Technologie, Laboratoire de Technologie Industrielle et de l'Information, Université de Bejaia, Targa ouzemour, 06000, Bejaia, Algeria
| | - Milkias Berhanu Tuka
- Department of Electrical Power and Control Engineering, Adama Science and Technology University, Adama, Ethiopia.
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Punyavathi R, Pandian A, Singh AR, Bajaj M, Tuka MB, Blazek V. Sustainable power management in light electric vehicles with hybrid energy storage and machine learning control. Sci Rep 2024; 14:5661. [PMID: 38454016 PMCID: PMC10920784 DOI: 10.1038/s41598-024-55988-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/29/2024] [Indexed: 03/09/2024] Open
Abstract
This paper presents a cutting-edge Sustainable Power Management System for Light Electric Vehicles (LEVs) using a Hybrid Energy Storage Solution (HESS) integrated with Machine Learning (ML)-enhanced control. The system's central feature is its ability to harness renewable energy sources, such as Photovoltaic (PV) panels and supercapacitors, which overcome traditional battery-dependent constraints. The proposed control algorithm orchestrates power sharing among the battery, supercapacitor, and PV sources, optimizing the utilization of available renewable energy and ensuring stringent voltage regulation of the DC bus. Notably, the ML-based control ensures precise torque and speed regulation, resulting in significantly reduced torque ripple and transient response times. In practical terms, the system maintains the DC bus voltage within a mere 2.7% deviation from the nominal value under various operating conditions, a substantial improvement over existing systems. Furthermore, the supercapacitor excels at managing rapid variations in load power, while the battery adjusts smoothly to meet the demands. Simulation results confirm the system's robust performance. The HESS effectively maintains voltage stability, even under the most challenging conditions. Additionally, its torque response is exceptionally robust, with negligible steady-state torque ripple and fast transient response times. The system also handles speed reversal commands efficiently, a vital feature for real-world applications. By showcasing these capabilities, the paper lays the groundwork for a more sustainable and efficient future for LEVs, suggesting pathways for scalable and advanced electric mobility solutions.
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Affiliation(s)
- R Punyavathi
- Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, 522302, India
| | - A Pandian
- Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, 522302, India
| | - Arvind R Singh
- Department of Electrical Engineering, School of Physics and Electronic Engineering, Hanjiang Normal University, Hubei Shiyan, 442000, People's Republic of China
| | - Mohit Bajaj
- Department of Electrical Engineering, Graphic Era (Deemed to Be University), Dehradun, 248002, India.
- Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
- Graphic Era Hill University, Dehradun, 248002, India.
- Applied Science Research Center, Applied Science Private University, Amman, 11937, Jordan.
| | - Milkias Berhanu Tuka
- Department of Electrical and Computer Engineering, College of Engineering, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.
| | - Vojtech Blazek
- ENET Centre, VSB-Technical University of Ostrava, 708 00, Ostrava, Czech Republic
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