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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 (∑-ANN) and product ( ∏ -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 ∏ -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. [ABSTRACT FROM AUTHOR]

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 (∑-ANN) and product ( ∏ -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 ∏ -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. [ABSTRACT FROM AUTHOR]

On a flat city road, the specificity of the suspension poses a challenge. Sport utility vehicles (SUVs) have less flexibility compared to regular cars, despite providing a firm grip on asphalt and concrete. Constant adjustments to the center of gravity of SUVs are necessary. Surprisingly, they are less reliable and stable in urban settings due to this characteristic. In this study, a mathematical model of the suspension system of SUVs based on the Newtonian approach is introduced and validated with data from experiments carried out by the MTS machine system on the mono-tube (oil/air) mixed damper element. The model accurately predicts the performance of this damper, commonly used in SUVs, across various operating conditions, including different frequencies. A coil spring element, serving as a passive suspension unit with this damper, is also tested experimentally under similar conditions. By integrating passive suspension elements with the active actuator, the proposed modified design reduces the power consumption needed for the actuator to function and ensures a certain level of reliability. The effectiveness and performance of the modified active suspension system in comparison to the traditional passive suspension system are assessed using three different strategies: hybrid PID-LQR, linear quadratic regulator (LQR), and proportional-integral-derivative (PID). The genetic algorithm is utilized to determine the optimal parameter values for each controller by minimizing a cost function, maximizing performance, and minimizing energy consumption. Simulation results demonstrate that the active suspension system controlled by the PID-LQR controller offers significantly improved ride comfort and vehicle stability compared to other systems. This suggests that the performance of the active suspension system is greatly enhanced by the combined application of the hybrid PID-LQR controller compared to other systems. [ABSTRACT FROM AUTHOR]

Cleaning products are mixtures of many chemical ingredients that are known to contain sensitizers, disinfectants, and fragrances, as well as strong airway irritants which associated with lower respiratory tract and asthma symptoms. The aim of this study is to assess the prevalence and possible risk factors of occupational asthma and its effect on quality of life among workers in detergent and cleaning products industries in El Asher men Ramadan city. This cross-sectional study was conducted on 780 workers. All participants were personally interviewed at their workplaces and were subjected to a questionnaire regarding sociodemographic, work characteristics and asthma symptoms, clinical examination, chest X-ray, spirometer, and bronchodilator test. The prevalence of occupational asthma among the studied workers was 35.4%. Multivariate logistic regression analysis revealed that female gender [odds ratio 1.397; 95% CI 1.09–1.96], manually working participants [odds ratio 3.067; 95% CI 1.72–5.46], and history of atopy [odds ratio 1.596; 95% CI 1.09–2.33] were risk factors for development of occupational asthma. The total mean score of asthma-specific quality of life was significantly lower in asthmatic (5.10 ± 0.49) than non-asthmatic workers (5.89 ± 0.46) (P < 0.01) indicating impairment of quality of life among asthmatic group. Workers in detergent and cleaning products industry are at higher risk for developing occupational asthma that adversely affects their general health and quality of life. [ABSTRACT FROM AUTHOR]