Purpose This study introduces a magneto-rheological (MR) semi-active seat suspension system integrated with the vehicle's suspension, considering the driver's biodynamics. The diverse range of passenger types leads to variations in biodynamic parameters, resulting in parametric uncertainties. The primary objective is to address these uncertainties by designing a damper controller that optimally adjusts the MR damper's voltage to achieve superior ride comfort and stability. Methods To manage parametric uncertainties, the study proposes a novel seat damper controller using inverse summation (& sum;-ANN) and product (& prod;-ANN) type neural networks. The performance of these controllers is compared against the conventional Signum function controller. The effectiveness of the proposed MR seat-controlled suspension system is evaluated in both internal combustion engine (ICE) vehicles and electric vehicles (EV), utilizing the main suspension system for analysis. A 2 T-FLS system controller is integrated to enhance control and improve ride quality across different vehicle types. Results Simulations demonstrate that the proposed MR seat suspension system, with the combined 2 T-FLS and & prod;-ANN damper controller, effectively minimizes vibrations and enhances ride comfort, especially in EVs. The findings also reveal that the engine vibration force caused by the gasoline-air mixture is harmful to ride comfort in ICE vehicles, whereas EVs exhibit strong dynamic stability due to less disruptive wheel vibrations generated by electric motors. Conclusion The study demonstrates the effectiveness of the proposed MR seat suspension system in enhancing ride quality and dynamic stability. The integration of the 2 T-FLS system controller with the MR seat suspension system offers superior damping control, improving ride quality for both ICE and EV vehicles. EVs benefit significantly due to their reduced engine vibration forces, emphasizing the system's potential to enhance passenger comfort and vehicle performance across diverse vehicle types.
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China Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R ChinaChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
Liu, Xinhua
Wang, Ningning
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China Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R ChinaChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
Wang, Ningning
Wang, Kun
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China Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R ChinaChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
Wang, Kun
Huang, Hui
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Fujian Prov Univ, Fuzhou Univ, Key Lab Fluid Power & Intelligent Electrohydraul, Fuzhou, Fujian, Peoples R ChinaChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
Huang, Hui
Li, Zhixiong
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Ocean Univ China, Dept Marine Engn, Tsingdao, Peoples R China
Univ Wollongong, Sch Mech Mat Mechatron & Biomed Engn, Wollongong, NSW, AustraliaChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
Li, Zhixiong
Sarkodie-Gyan, Thompson
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Univ Texas El Paso, Dept Elect & Comp Engn, Coll Engn, El Paso, TX 79968 USAChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
Sarkodie-Gyan, Thompson
Li, Weihua
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Univ Wollongong, Sch Mech Mat Mechatron & Biomed Engn, Wollongong, NSW, AustraliaChina Univ Min & Technol, Sch Mech & Elect Engn, Xuzhou, Jiangsu, Peoples R China
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Menoufia Univ, Fac Elect Engn, Dept Ind Elect & Control Engn, Menoufia 32952, EgyptMenoufia Univ, Fac Elect Engn, Dept Ind Elect & Control Engn, Menoufia 32952, Egypt
Abd-Elhaleem, Sameh
Shoeib, Walaa
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Menoufia Univ, Fac Elect Engn, Dept Ind Elect & Control Engn, Menoufia 32952, EgyptMenoufia Univ, Fac Elect Engn, Dept Ind Elect & Control Engn, Menoufia 32952, Egypt
Shoeib, Walaa
Sobaih, Abdel Azim
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Menoufia Univ, Fac Elect Engn, Dept Ind Elect & Control Engn, Menoufia 32952, EgyptMenoufia Univ, Fac Elect Engn, Dept Ind Elect & Control Engn, Menoufia 32952, Egypt