DESIGN AND IMPLEMENTATION OF A ZERO EMISSION VEHICLE INTEGRATED WITH MULTIPLE ENERGY SOURCES

Authors

  • David Enemali Abah
    Ahmadu Bello University, Zaria
  • Yusuf Sani Abu
    Federal University Dutsin-Ma image/svg+xml
  • Musa Adamu Ndalami
    Ahmadu Bello University, Zaria
  • Ahmad Aminu Abba
    Ahmadu Bello University, Zaria
  • Abdulkadir Kabir
    Federal Polytechnic, Kaura Namoda
  • Mahmud Isa
    Federal Polytechnic, Kaura Namoda
  • Adeseye Bamidele Niyi
    National Research Institute for Chemical Technology, Zaria

Keywords:

Energy management system, Zero-emission, Hybrid Electric Vehicle, State of charge, Multiple energy sources

Abstract

Due to the rising fuel prices, there is a global shift towards the adoption of hybrid electric vehicles (HEVs) because of their environmental benefits, lower maintenance needs, and alignment with green technology. In HEVs, the energy management system (EMS) is crucial for ensuring efficient energy storage and managing the power flow between the different energy sources, such as the internal combustion engine, battery, and electric motor. The EMS optimizes energy usage, enhances overall vehicle efficiency, and contributes to reducing fuel consumption and emissions, playing a pivotal role in the performance and sustainability of HEVs. This research work proposes an electric vehicle concept powered by multiple energy sources. The design will integrate solar photovoltaic (PV) energy, wind turbine and a fuel cell (FC), (PV + FC) to generate electrical energy. The vehicle will incorporate onboard solar panels, wind energy systems, proton exchange membrane (PEM) fuel cell and supercapacitor units to ensure uninterrupted energy supply during operation which can be achieved with fuzzy-based EMS. Poor design of the EMS will have effect on the performance limitations of the battery state of charge (SOC), and not fully optimizing energy recovery during braking will result in lower overall energy efficiency. This work addresses the above challenges by using fuzzy-EMS. The Simulation results showcase the system’s ability to achieve zero emissions, reduce operational costs, and promote environmental sustainability.

Dimensions

Abbassi, R., Abbassi, A., Heidari, A. A., & Mirjalili, S. (2019). An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models. Energy Conversion and Management, 179(August 2018), 362372. https://doi.org/10.1016/j.enconman.2018.10.069

Abulifa, A. A. (2017). Modelling and Simulation of Battery Electric Vehicle by Using MATLAB-Simulink. IEEE International Conference on Computing, Power and Communication Technologies (GUCON), 383387.

Adedeji, B. P. (2024). Energy parameter modeling in plug-in hybrid electric vehicles using supervised machine learning approaches. E-Prime - Advances in Electrical Engineering, Electronics and Energy, 8(January), 100584. https://doi.org/10.1016/j.prime.2024.100584

Albatayneh, A., Assaf, M. N., Alterman, D., & Jaradat, M. (2020). Comparison of the Overall Energy Efficiency for Internal Combustion Engine Vehicles and Electric Vehicles. Environmental and Climate Technologies, 24(1), 669680. https://doi.org/10.2478/rtuect-2020-0041

Binkowski, T. (2020). A conductance-based MPPT method with reduced impact of the voltage ripple for one-phase solar powered vehicle or aircraft systems. Energies, 13(6). https://doi.org/10.3390/en13061496

Chakir, A., Abid, M., Tabaa, M., & Hachimi, H. (2022). ScienceDirect Demand-side management strategy in a smart home using electric vehicle and hybrid renewable energy system. Energy Reports, 8(May), 383393. https://doi.org/10.1016/j.egyr.2022.07.018

Chandrasekar, B., Nallaperumal, C., Padmanaban, S., Bhaskar, M. S., Holm-Nielsen, J. B., Leonowicz, Z., & Masebinu, S. O. (2020). Non-Isolated High-Gain Triple Port DC-DC Buck-Boost Converter with Positive Output Voltage for Photovoltaic Applications. IEEE Access, 8, 113649113666. https://doi.org/10.1109/ACCESS.2020.3003192

Chen, Z., Xiong, R., Wang, K., & Jiao, B. (2015). Optimal energy management strategy of a plug-in hybrid electric vehicle based on a particle swarm optimization algorithm. Energies, 8(5), 36613678. https://doi.org/10.3390/en8053661

De Carvalho Pinheiro, H. (2023). PerfECT Design Tool: Electric Vehicle Modelling and Experimental Validation. World Electric Vehicle Journal, 14(12). https://doi.org/10.3390/wevj14120337

Eseye, A. T., Lehtonen, M., Tukia, T., Uimonen, S., & Millar, R. J. (2019). Optimal Energy Trading for Renewable Energy Integrated Building Microgrids Containing Electric Vehicles and Energy Storage Batteries. IEEE Access, 19. https://doi.org/10.1109/ACCESS.2019.2932461

Gultom, T. H., Nugraha, D., Sugiyarno, & Iqbal, M. (2023). Contribution of Obi Island Reducing the Carbon Footprint in the Transport Sector. IOP Conference Series: Earth and Environmental Science, 1175(1). https://doi.org/10.1088/1755-1315/1175/1/012015

Gupta, N., Member, S., & Simulation, M. C. (2020). Probabilistic optimal reactive power planning with onshore and offshore wind generation , EV and PV uncertainties. IEEE, 9994(c), 114. https://doi.org/10.1109/TIA.2020.2985319

Hasanien, H. M., & El-Fergany, A. A. (2019). Salp swarm algorithm-based optimal load frequency control of hybrid renewable power systems with communication delay and excitation cross-coupling effect. Electric Power Systems Research, 176(October 2018), 105938. https://doi.org/10.1016/j.epsr.2019.105938

Horrein, L., Bouscayrol, A., Cheng, Y., Dumand, C., Colin, G., & Chamaillard, Y. (2016). Influence of the heating system on the fuel consumption of a hybrid electric vehicle. Energy Conversion and Management, 129, 250261. https://doi.org/10.1016/j.enconman.2016.10.030

Hu, Z., Li, J., Xu, L., Song, Z., Fang, C., Ouyang, M., Dou, G., & Kou, G. (2016). Multi-objective energy management optimization and parameter sizing for proton exchange membrane hybrid fuel cell vehicles. Energy Conversion and Management, 129, 108121. https://doi.org/10.1016/j.enconman.2016.09.082

Huang, Z., & Zhang, C. (2019). Modeling and energy management of a photovoltaic-fuel cell-battery hybrid electric vehicle. Energy Storage Wiley, April. https://doi.org/10.1002/est2.61

Ibrahim, M. H., Ang, S. P., Dani, M. N., Rahman, M. I., Petra, R., & Sulthan, S. M. (2023). Optimizing Step-Size of Perturb & Observe and Incremental Conductance MPPT Techniques Using PSO for Grid-Tied PV System. IEEE Access, 11(January), 1307913090. https://doi.org/10.1109/ACCESS.2023.3242979

Ishaque, M. R., Khan, M. A., Afzal, M. M., Wadood, A., Oh, S. R., Talha, M., & Rhee, S. B. (2021). Fuzzy logic-based duty cycle controller for the energy management system of hybrid electric vehicles with hybrid energy storage system. Applied Sciences (Switzerland), 11(7). https://doi.org/10.3390/app11073192

Jadhav, A. D., & Nair, S. (2019). Battery Management using Fuzzy Logic Controller. Journal of Physics: Conference Series, 1172(1). https://doi.org/10.1088/1742-6596/1172/1/012093

Kandidayeni, M., Macias, A., Boulon, L., & Trovo, J. P. F. (2020). Online modeling of a fuel cell system for an energy management strategy design. Energies, 13(14), 117. https://doi.org/10.3390/en13143713

Kasoju, B. K. (2021). Simulation of Electric Vehicle Drive with Matlab / Simulink Simulation of Electric Vehicle Drive with Matlab / Simulink Kasoju Bharath Kumar. International Journal of Advances in Engineering and Management (IJAEM), June 2020. https://doi.org/10.35629/5252-45122323

Khan, K., & Samuilik, I. (2024). A Mathematical Model for Dynamic Electric Vehicles: Analysis and Optimization. Mathematics, 12(January), 119. https://doi.org/10.3390/ math12020224

Li, Y., Yang, J., & Song, J. (2017). Nano energy system model and nanoscale effect of graphene battery in renewable energy electric vehicle. Renewable and Sustainable Energy Reviews, 69(August 2015), 652663. https://doi.org/10.1016/j.rser.2016.11.118

Mamun, K. A., Islam, F. R., Haque, R., Chand, A. A., Prasad, K. A., Goundar, K. K., Prakash, K., & Maharaj, S. (2022). Systematic Modeling and Analysis of On-Board Vehicle Integrated Novel Hybrid Renewable Energy System with Storage for Electric Vehicles. Sustainability (Switzerland), 14(5), 133. https://doi.org/10.3390/su14052538

Marzougui, H., Kadri, A., Martin, J. P., Amari, M., Pierfederici, S., & Bacha, F. (2019). Implementation of energy management strategy of hybrid power source for electrical vehicle. Energy Conversion and Management, 195(May), 830843. https://doi.org/10.1016/j.enconman.2019.05.037

Mou, X., Zhang, Y., & Jiang, J. (2020). Achieving Low Carbon Emission for Dynamically Charging Electric Vehicles through Renewable Energy Integration. IEEE Access, PP, 1. https://doi.org/10.1109/ACCESS.2019.2936935

Pirpoor, S., Rahimpour, S., Andi, M., Kanagaraj, N., Pirouzi, S., & Mohammed, A. H. (2022). A Novel and High-Gain Switched-Capacitor and Switched-Inductor-Based DC/DC Boost Converter With Low Input Current Ripple and Mitigated Voltage Stresses. IEEE Access, 10, 3278232802. https://doi.org/10.1109/ACCESS.2022.3161576

Rafael, Z., & Carri, M. (2015). Operation of renewable-dominated power systems with a signi fi cant penetration of plug-in electric vehicles. Energies. https://doi.org/10.1016/j.energy.2015.07.111

Rahbari, O., Vafaeipour, M., Omar, N., Rosen, M. A., Hegazy, O., Timmermans, J., Heibati, M., & Bossche, P. Van Den. (2017). An optimal versatile control approach for plug-in electric vehicles to integrate renewable energy sources and smart grids Highlights: Energy. https://doi.org/10.1016/j.energy.2017.06.007

Ravichandran, A., Sirouspour, S., Malysz, P., & Emadi, A. (2016). A Chance-Constraints-Based Control Strategy for Microgrids with Energy Storage and Integrated Electric Vehicles. IEEE, 3053(c), 114. https://doi.org/10.1109/TSG.2016.2552173

Sanguesa, J. A., Torres-sanz, V., Garrido, P., Martinez, F. J., & Marquez-barja, J. M. (2021). smart cities A Review on Electric Vehicles: Technologies and Challenges. MDPI, 372404.

Vinod, Kumar, R., & Singh, S. K. (2018). Solar photovoltaic modeling and simulation: As a renewable energy solution. Energy Reports, 4, 701712. https://doi.org/10.1016/j.egyr.2018.09.008

Wu, J., Ruan, J., Zhang, N., & Walker, P. D. (2018). An Optimized Real-Time Energy Management Strategy for the Power-Split Hybrid Electric Vehicles. IEEE Transactions on Control Systems Technology, 27(3), 11941202. https://doi.org/10.1109/TCST.2018.2796551

Yilmaz, M., Celikel, R., & Gundogdu, A. (2023). Enhanced Photovoltaic Systems Performance: Anti-Windup PI Controller in ANN-Based ARV MPPT Method. IEEE Access, 11(August), 9049890509. https://doi.org/10.1109/ACCESS.2023.3290316

Yin, H., Zhou, W., Li, M., & Zhao, C. (2015). An Adaptive Fuzzy Logic Based Energy Management Strategy on Battery / Ultracapacitor Hybrid Electric Vehicles. IEEE Transactions on Transportation Electrification, 7782(c), 112. https://doi.org/10.1109/TTE.2016.2552721

Zheng, C., Li, W., & Liang, Q. (2018). An Energy Management Strategy of Hybrid Energy Storage Systems for Electric Vehicle Applications. IEEE Transactions on Sustainable Energy, 9(4), 18801888. https://doi.org/10.1109/TSTE.2018.2818259

Published

21-08-2025

How to Cite

DESIGN AND IMPLEMENTATION OF A ZERO EMISSION VEHICLE INTEGRATED WITH MULTIPLE ENERGY SOURCES. (2025). FUDMA JOURNAL OF SCIENCES, 9(8), 303-321. https://doi.org/10.33003/fjs-2025-0908-3926

Issue

Vol. 9 No. 8 (2025): FUDMA Journal of Sciences - Vol. 9 No. 8

Section

Research Articles
Copyright & Licensing

FUDMA Journal of Sciences

How to Cite

DESIGN AND IMPLEMENTATION OF A ZERO EMISSION VEHICLE INTEGRATED WITH MULTIPLE ENERGY SOURCES. (2025). FUDMA JOURNAL OF SCIENCES, 9(8), 303-321. https://doi.org/10.33003/fjs-2025-0908-3926

Most read articles by the same author(s)