Modeling and Simulation of a Semi-active Vehicle Suspension system using PID Controller

Narwade, Prashant; Deshmukh, Ravindra R.; Nagarkar, Mahesh; Bankar, Milind A

doi:10.1088/1757-899x/1004/1/012003

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…As shown in Figure 6b, when the active control circuit in the energy recovery actuator works, the load of the energy recovery motor is the car battery, and the car battery supplies power to the energy recovery motor. St this time the active control force is shown in Equation (11), and the voltage U at both ends of the energy recovery motor is shown in Equation (17).…”

Section: Mathematical Model For Active Controlmentioning

confidence: 99%

“…Among various active control algorithms, the PID controller is widely used because of its simple algorithm, stable control ability, good robustness and other advantages. Narwade [11] studied the modelling and simulation of an automotive semi-active suspension system based on the PID controller, and conducted a simulation study for the application of the PID controller on automotive suspension in a more systematic way. Nagarkar [12] used PID and fuzzy control, based on a genetic algorithm, for an active non-linear 1/4 automotive suspension system to achieve multi-objective optimization of the suspension system.…”

Section: Introductionmentioning

confidence: 99%

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Fractional Order PID Control Based on Ball Screw Energy Regenerative Active Suspension

Zhang

Liu²,

Liu³

et al. 2022

Actuators

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A ball screw type energy regenerative active suspension under fractional order PID control is proposed and studied in order to improve the vibration damping performance of the suspension. A mathematical model of the energy regenerative actuator is established, the energy recovery power at different frequencies is measured through experiments, and then the electromagnetic torque constant, representing the proportional relationship between the output torque and current of the motor, is calculated according to the experimental results. A mathematical model of the control circuit is established and the feasibility and the superiority of the fractional order PID control are verified by simulation and experiments. To achieve a better damping effect, the fractional order PID controller of the whole vehicle suspension system is parameterized using the Beetle Antenna Search (BAS) algorithm. The results showed that the mean energy recovery power of the actuator was about 3.5091 W at a vibration frequency of 11/6 Hz, and the electromagnetic torque constant of the motor was about 0.2885. The actuator control circuit was feasible, and the root mean square value of current deviation under fractional order PID control was 1.1158 mA, which was optimized by 9.40%, compared to the PID control. The BAS algorithm effectively realized the parameter tuning of the controller, and both the tuned PID and fractional order PID controllers, achieved optimization of suspension damping performance. The optimal value of the damping performance objective function under fractional order PID control was 0.3270, which was optimized by 62.93%, compared to the PID control. In addition, all suspension performance indices under fractional order PID control were optimized to a certain extent, compared with the PID control.

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Section: Mathematical Model For Active Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fractional Order PID Control Based on Ball Screw Energy Regenerative Active Suspension

Zhang

Liu²,

Liu³

et al. 2022

Actuators

View full text Add to dashboard Cite

show abstract

“…Currently, the hardware part of the field is relatively mature, and the research focuses on further enhancement of its control algorithms. In order to improve the suspension system drooping dynamics performance, Narwade et al [ 9 ] studied the modeling and simulation of an automotive semiactive suspension system based on a PID controller and carried out the simulation study of the PID controller’s application for automotive suspensions in a more systematic way; Li et al [ 10 ] used a genetic algorithm to tune the PID controller and the fuzzy control theory for nonlinear suspension system control to achieve multiobjective optimization of a suspension system. Liu et al [ 11 ] proposed an adaptive neural network control scheme for active suspension with time-varying vertical displacement and velocity constraints as well as an active suspension system with an unknown body mass, and the feasibility and reasonableness of the proposed method were verified by simulation.…”

Section: Introductionmentioning

confidence: 99%

Research on Electric Oil–Pneumatic Active Suspension Based on Fractional-Order PID Position Control

Hu,

Liu,

Wang

et al. 2024

Sensors

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In this study, an electric oil and gas actuator based on fractional-order PID position feedback control is proposed, through which the damping coefficient of the suspension system is adjusted to realize the active control of the suspension. An FOPID algorithm is used to control the motor’s rotational angle to realize the damping adjustment of the suspension system. In this process, the road roughness is collected by the sensors as the criterion of damping adjustment, and the particle swarm algorithm is utilized to find the optimal objective function under different road surface slopes, to obtain the optimal cornering value. According to the mathematical and physical model of the suspension system, the simulation model and the corresponding test platform of this type of suspension system are built. The simulation and experimental results show that the simulation results of the fractional-order nonlinear suspension model are closer to the actual experimental values than those of the traditional linear suspension model, and the accuracy of each performance index is improved by more than 18.5%. The designed active suspension system optimizes the body acceleration, suspension dynamic deflection, and tire dynamic load to 89.8%, 56.7%, and 73.4% of the passive suspension, respectively. It is worth noting that, compared to traditional PID control circuits, the FOPID control circuit designed for motors has an improved control performance. This study provides an effective theoretical and empirical basis for the control and optimization of fractional-order nonlinear suspension systems.

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Design and Optimization of Spring in Damping System of New Energy Electric Vehicle

Chiu

et al. 2022

Advances in Intelligent Information Hiding and Multimedia Signal Processing

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Modeling and Simulation of a Semi-active Vehicle Suspension system using PID Controller

Cited by 4 publications

References 4 publications

Fractional Order PID Control Based on Ball Screw Energy Regenerative Active Suspension

Fractional Order PID Control Based on Ball Screw Energy Regenerative Active Suspension

Research on Electric Oil–Pneumatic Active Suspension Based on Fractional-Order PID Position Control

Design and Optimization of Spring in Damping System of New Energy Electric Vehicle

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