Several studies exist on topics of semi-active suspension and vehicle cruise control systems in the literature, while many of them just consider actual road distortions and terrain characteristics, these systems are not adaptive and their subsystems designed separately. This study introduces a new method where the integration of look-ahead road data in the control of the adaptive semi-active suspension, where it is possible to the trade-off between comfort and stability orientation. This trade-off is designed by the decision layer, where the controller is modified based on prehistorical passive suspension simulations, vehicle velocity and road data, while the behavior of the controller can be modified by the use of a dedicated scheduling variable. The adaptive semi-active suspension control is designed by using Linear Parameter Varying (LPV) framework. In addition to this, it proposes designing the vehicle velocity for the cruise controller by considering energy efficiency and comfort together. TruckSim environment is used to validate the operation of the proposed integrated cruise and semi-active suspension control system.

Adaptive Semi-Active Suspension and Cruise Control through LPV Technique

This paper introduces a novel method to control the operation of the active suspension system. In this research, a quarter-dynamic model is used to simulate the vehicle’s vibrations. Besides, the sliding mode-PID-integrated algorithm with five state variables is proposed to be used. This is a completely original and novel algorithm. The process of establishing the control algorithm is clearly described. The simulation is performed by the MATLAB software. The results of the paper have shown the advantages of the sliding mode-PID algorithm used in this research. Accordingly, the displacement and acceleration of the sprung mass were significantly reduced when this algorithm was used. The maximum and average values of the displacement of the sprung mass are only 1.31% and 1.29%, respectively, compared with the situation of the vehicle using a passive suspension. Similarly, the value of the acceleration is 6.98% and 2.94%, respectively. In addition, the phenomenon of “chattering” has also been significantly reduced when using this controller. In the future, some more complex algorithms can be proposed.

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A Novel Hybrid Control Algorithm Sliding Mode-PID for the Active Suspension System with State Multivariable

This study introduces an online reconfigurable road-adaptive semi-active suspension controller that reaches the performance objectives with satisfying the dissipativity constraint. The concept of the model is based on a nonlinear static model of the semi-active Magnetorheological (MR) damper with considering the bi-viscous and hysteretic behaviors of the damper. The input saturation problem has been solved by using the proposed method in the literature that allows the integration of the saturation actuator in the initial system to create a Linear Parameter Varying (LPV) system. The control input meets the saturation constraint; therewith, the dissipativity constraint is fulfilled. The online reconfiguration and adaptivity problem is solved by using an external scheduling variable that allows the trade-off between driving comfort and road holding/stability. The control design is based on the LPV framework. The proposed adaptive semi-active suspension controller is compared to passive suspension and Bingham model with Simulink simulation, and then the adaptivity of the controller is validated with the TruckSim environment. The results show that the proposed LPV controller has better performance results than the controlled Bingham and passive semi-active suspension model.

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An LPV-Based Online Reconfigurable Adaptive Semi-Active Suspension Control with MR Damper

In hub-motor electric vehicles (HM-EVs), the unbalanced electromagnetic force generated by the HM will further deteriorate the dynamic performance of the electric vehicle. In this paper, a semiactive suspension control method is proposed for HM-EVs. A quarter HM-EV model with an electromechanical coupling effect is established.The model consists of three parts: a motor model, road excitation model and vehicle model. A hybrid model predictive controller (HMPC) is designed based on the developed model, taking into account the nonlinear constraints of damping force. The focus is on improving the vertical performance of the HM-EV. Then, a Kalman filter is designed to provide the required state variables for the controller. The proposed control algorithm and constrained optimal control (COC) algorithm are simulation compared under random road excitation and bump road excitation, and the results show that the proposed control algorithm can improve ride comfort, reduce motor vibration, and improve handling stability more substantially.

Hybrid Model Predictive Control of Semiactive Suspension in Electric Vehicle with Hub-Motor

The purpose of the present work was to design, optimize, and test an innovative suspension system for race cars. The study was based on a comprehensive approach that involved conceptual design, modeling, simulation and optimization, and development and testing of the experimental model of the proposed suspension system. The optimization process was approached through multi-objective optimal design techniques, based on design of experiments (DOE) investigation strategies and regression models. At the same time, a synthesis method based on the least squares approach was developed and integrated in the optimal design algorithm. The design in the virtual environment was achieved by using the multi-body systems (MBS) software package ADAMS, more precisely ADAMS/View—for modeling and simulation, and ADAMS/Insight—for multi-objective optimization. The physical prototype of proposed suspension system was implemented and tested with the help of BlueStreamline, the Formula Student race car of the Transilvania University of Brașov. The dynamic behavior of the prototype was evaluated by specific experimental tests, similar to those the single seater would have to pass through in the competitions. Both the virtual and experimental results proved the performance of the proposed suspension system, as well as the usefulness of the design algorithm by which the novel suspension was developed.

Multi-Criteria Optimization of an Innovative Suspension System for Race Cars

In this work, four different semi-active controllers for a quarter of vehicle and full vehicles are evaluated and compared when used in internal combustion engine (ICE) vehicles vs electric vehicles (EVs) with in-wheel motor configuration as a way to explore the use of semi-active suspension systems in this kind of EVs First, the quarter of vehicle vertical dynamics is analyzed and then a full vehicle approach explores the effectiveness of the control strategies and the effects of the traction in the vertical Control performances Aspects like the relation between traction and suspension performances, and the resonance frequencies are also discussed

https://www.mdpi.com/2076-3417/10/13/4522/pdf

Mauricio Anaya-Martinez

Papers

Control of Automotive Semi-Active MR Suspensions for In-Wheel Electric Vehicles