Artificial Intelligent in Automotive Suspension System for Vertical Body Vibration Improvement using Neural Network
Keywords:
Artificial intelligence (AI), neural networks (NN), automotive suspension system, vertical body vibration, vibration reductionAbstract
Introduction/Main Objectives: Vehicle suspension systems are essential for maintaining ride comfort and stability. Conventional passive systems often fail to adapt to varying road conditions, leading to compromises in performance. Artificial Intelligence (AI), particularly Neural Networks (NN), offers a promising solution for modelling nonlinear dynamics and enabling adaptive control in suspension systems. The main objectives are to apply AI techniques using Neural Networks for optimizing suspension performance, to model and analyze a two-degree-of-freedom (2DOF) vertical body vibration system based on a quarter-car model and to improve ride comfort and stability by minimizing body acceleration and tire load variations.
Background Problems: Traditional suspension systems lack adaptability and struggle to balance comfort with handling. Road irregularities introduce nonlinear vibrations that passive systems cannot effectively mitigate. This creates a need for intelligent, real-time control strategies.
Research Methods: A two-degree-of-freedom (2DOF) quarter-car model was developed to represent the dynamic interaction between the sprung and unsprung masses. Simulation data were generated under various road excitation conditions to capture the system’s response to real-world disturbances. A feedforward neural network was then trained using this data to predict optimal suspension responses, enabling adaptive control strategies. Finally, the performance of the AI-based suspension system was compared with that of a conventional passive suspension system to evaluate improvements in ride comfort and stability.
Finding/Results: The neural network successfully learned complex nonlinear relationships within suspension dynamics. AI-based control strategies demonstrated superior performance in reducing body acceleration and maintaining tire contact compared to passive systems, resulting in improved ride quality.
Conclusion: AI-driven suspension systems using Neural Networks provide an effective framework for real-time vibration control. This approach enhances comfort and stability, paving the way for next-generation intelligent vehicles.
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