An experimental approach of estimating speed bump profile to optimizing the suspension parameters using TLBO

Vedant Mehta, Mayuri Patel, Yash Gandhi, Bhargav Gadhvi


This paper implements an experimental approach to collect data of acceleration vs. time. The data obtained is fed into the bump estimator model to obtain a speed bump profile. Further, this profile is given as an input to the active suspension model, which is used in optimizing the suspension parameter with the help of TLBO (Teaching-Learning based Optimization algorithm). By controlling the parameters, the ride comfort and vehicle handling can be improved. PID controller controls the actuator force to be applied while travelling but using optimized suspension parameters reduces the actuator force to be applied, as well as the rattle space. The mathematical model of the car is modeled into MATLAB/Simulink environment. There is much future scope related to the experimental method, which is discussed in this paper as well. 

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