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Recovering waste vibration energy of an automobile using shock absorbers included magnet moving-coil mechanism and adding to overall efficiency using wind turbine

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  • Fathabadi, Hassan

Abstract

The vibration energy of an automobile caused by driving on bumpy roads and the automobile acceleration as well as its deceleration is dissipated by the shock absorbers of the automobile, so the vibration energy is wasted in the suspension system of the automobile. This paper deals with increasing the energy efficiency of an automobile by applying two modifications to the automobile. First, to recover the mentioned waste vibration energy, magnet moving-coil mechanism is added to the four shock absorbers of the automobile by embedding four proposed electric coils inside the four shock absorbers. The total electric voltage of the four electric coils is converted into a constant dc voltage technically named “dc-link voltage” using a converter. Second, to recover a part of the kinetic energy of wind hitting the automobile when the automobile is moving or stopping, a wind turbine is attached to the back of the automobile’s condenser. Correspondingly, the output voltage of the wind turbine is converted into the dc-link voltage using another converter. By constructing a novel system including the two mentioned converters, the power productions of the four electric coils and wind turbine are converted into appropriate levels of voltage and current to be used to charge the battery of the automobile as well as to drive the other parts of the automobile. The two modifications can be applied to both internal combustion engine vehicles and electric vehicles (EVs). Experimental measurements obtained from applying the two mentioned modifications and the constructed system to an EV with the weight of 1855 kg are presented that demonstrate the four electric coils and wind turbine have added respectively 0.36 kWh and 2.64 kWh to the energy production in the EV during two days, and as a result, the traveling range of the EV has increased by 7.27 km. This point proves the advantage of utilizing the proposed electric coils and wind turbine as well as the novelty and contribution of this study in recapturing the waste vibration energy of an automobile and the energy of wind hitting the automobile.

Suggested Citation

  • Fathabadi, Hassan, 2019. "Recovering waste vibration energy of an automobile using shock absorbers included magnet moving-coil mechanism and adding to overall efficiency using wind turbine," Energy, Elsevier, vol. 189(C).
  • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319693
    DOI: 10.1016/j.energy.2019.116274
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    References listed on IDEAS

    as
    1. Fathabadi, Hassan, 2020. "Novel solar-powered photovoltaic/thermoelectric hybrid power source," Renewable Energy, Elsevier, vol. 146(C), pages 426-434.
    2. Fathabadi, Hassan, 2017. "Novel standalone hybrid solar/wind/fuel cell/battery power generation system," Energy, Elsevier, vol. 140(P1), pages 454-465.
    3. Yip, Chak Man Andrew & Gunturu, Udaya Bhaskar & Stenchikov, Georgiy L., 2016. "Wind resource characterization in the Arabian Peninsula," Applied Energy, Elsevier, vol. 164(C), pages 826-836.
    4. Dalibor Petković & Siti Ab Hamid & Žarko Ćojbašić & Nenad Pavlović, 2014. "Adapting project management method and ANFIS strategy for variables selection and analyzing wind turbine wake effect," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 463-475, November.
    5. Fathabadi, Hassan, 2016. "Novel high-efficient unified maximum power point tracking controller for hybrid fuel cell/wind systems," Applied Energy, Elsevier, vol. 183(C), pages 1498-1510.
    6. Fathabadi, Hassan, 2018. "Novel fuel cell/battery/supercapacitor hybrid power source for fuel cell hybrid electric vehicles," Energy, Elsevier, vol. 143(C), pages 467-477.
    7. Petković, Dalibor & Ćojbašič, Žarko & Nikolić, Vlastimir, 2013. "Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 191-195.
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