Comprehensive Analysis for Influence of Controllable Damper Time Delay on Semi-Active Suspension Control Strategies

This paper presents a comprehensive comparison and analysis for the effect of time delay on the five most representative semi-active suspension control strategies, and refers to four unsolved problems related to semi-active suspension performance and delay mechanism that existed. Dynamic characteristics of a commercially available continuous damping control (CDC) damper were first studied, and a material test system (MTS) load frame was used to depict the velocity-force map for a CDC damper. Both inverse and boundary models were developed to determine dynamic characteristics of the damper. In addition, in order for an improper damper delay of the form t+τ to be corrected, a delay mechanism of controllable damper was discussed in detail. Numerical simulation for five control strategies, i.e., modified skyhook control SC, hybrid control (HC), COC, model reference sliding mode control (MRSMC), and integrated error neuro control (IENC), with three different time delays: 5 ms, 10 ms, and 15 ms was performed. Simulation results displayed that by changing control weights/variables, performance of all five control strategies varied from being ride comfort oriented to being road handling oriented. Furthermore, increase in delay time resulted in deterioration of both ride comfort and road handling. Specifically, ride comfort was affected more than road handling. The answers to all four questions were finally provided according to simulation results.

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Active Vehicle Suspension with Anti-Roll System Based on Advanced Sliding Mode Controller

Energies ◽

10.3390/en13215560 ◽

2020 ◽

Vol 13 (21) ◽

pp. 5560

Author(s):

Jarosław Konieczny ◽

Marek Sibielak ◽

Waldemar Rączka

Keyword(s):

Ride Comfort ◽

Sliding Mode ◽

Synthesis Method ◽

Active Suspension ◽

Vehicle Suspension ◽

Sliding Mode Controller ◽

Energy Consumption Optimization ◽

Suspension Control ◽

Vertical Displacements ◽

Linear Regulators

In the paper authors consider the active suspension of the wheeled vehicle. The proposed controller consists of a sliding mode controller used to roll reduction and linear regulators with quadratic performance index (LQRs) for struts control was shown. The energy consumption optimization was taken into account at the stage of strut controllers synthesis. The studied system is half of the active vehicle suspension using hydraulic actuators to increase the ride comfort and keeping safety. Instead of installing additional actuators in the form of active anti-roll bars, it has been decided to expand the active suspension control algorithm by adding extra functionality that accounts for the roll. The suggested algorithm synthesis method is based on the object decomposition into two subsystems whose controllers can be synthesized separately. Individual suspension struts are controlled by actuators that use the controllers whose parameters have been calculated with the LQR method. The mathematical model of the actuator applied in the work takes into account its nonlinear nature and the dynamics of the servovalve. The simulation tests of the built active suspension control system have been performed. In the proposed solution, the vertical displacements caused by uneven road surface are reduced by controllers related directly to suspension strut actuators.

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The Implementation of Skyhook Control for Semi-Active Suspension Based on Vi-CarRealTime

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.713-715.748 ◽

2015 ◽

Vol 713-715 ◽

pp. 748-751 ◽

Cited By ~ 1

Author(s):

Bo Wei Bi ◽

Fang Xiao

Keyword(s):

Control Strategy ◽

Ride Comfort ◽

Active Suspension ◽

Vehicle Model ◽

Control Range ◽

Control Signals ◽

Suspension Control ◽

Automobile Suspension ◽

Simulation Results ◽

Damper Control

The research of semi active suspension control strategy once was a hot point in the field of automobile suspension [2, 3], but it is difficult to achieve for most of them. I choose VI-CarRealTime to build vehicle model based on ADAMS vehicle model. Kalman Filter designed based on 1/2 vehicle model supply control signals for controller. Considering characteristics of CDC damper, Skyhook control strategy is applied for simulation, the simulation results show that, Skyhook Control can improve vehicle ride comfort in CDC damper control range.

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Based on Single Neuron PID Control of Vehicle Active Suspension System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.380-384.528 ◽

2013 ◽

Vol 380-384 ◽

pp. 528-531 ◽

Cited By ~ 1

Author(s):

Xiao Feng Liu ◽

Xin Hua Xie

Keyword(s):

Control Strategy ◽

Pid Control ◽

Single Neuron ◽

Ride Comfort ◽

Control Strategies ◽

Active Suspension ◽

Vital Role ◽

Suspension System ◽

Suspension Control ◽

Single Neuron Pid

Relative to the passive suspension, automotive active suspension car driving more ride comfort and stability, has a vital role to further improve the performance of the vehicle. For such a typically complex active suspension system research, the key issue is the selection of control strategies. The problems in the currently active suspension control strategy, the principle of a simple, effective, this paper, a single neuron PID control strategy used in the automotive active suspension system. The results show that compared with other control strategies, single neuron PID control strategy is reliable, has more advantages.

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Online Adaptive Neuro-Fuzzy Based Full Car Suspension Control Strategy

Research Methods ◽

10.4018/978-1-4666-7456-1.ch044 ◽

2015 ◽

pp. 992-1039

Author(s):

Laiq Khan ◽

Shahid Qamar

Keyword(s):

Degrees Of Freedom ◽

Ride Comfort ◽

Sliding Mode ◽

Active Suspension ◽

Suspension System ◽

Car Model ◽

Car Suspension ◽

Neuro Fuzzy ◽

Suspension Control ◽

Soft Computing Technique

Suspension system of a vehicle is used to minimize the effect of different road disturbances for ride comfort and improvement of vehicle control. A passive suspension system responds only to the deflection of the strut. The main objective of this work is to design an efficient active suspension control for a full car model with 8-Degrees Of Freedom (DOF) using adaptive soft-computing technique. So, in this study, an Adaptive Neuro-Fuzzy based Sliding Mode Control (ANFSMC) strategy is used for full car active suspension control to improve the ride comfort and vehicle stability. The detailed mathematical model of ANFSMC has been developed and successfully applied to a full car model. The robustness of the presented ANFSMC has been proved on the basis of different performance indices. The analysis of MATLAB/SMULINK based simulation results reveals that the proposed ANFSMC has better ride comfort and vehicle handling as compared to Adaptive PID (APID), Adaptive Mamdani Fuzzy Logic (AMFL), passive, and semi-active suspension systems. The performance of the active suspension has been optimized in terms of displacement of seat, heave, pitch, and roll.

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Active Suspension Control Based on Particle Swarm Optimization

Recent Patents on Mechanical Engineering ◽

10.2174/2212797612666191118123838 ◽

2020 ◽

Vol 13 (1) ◽

pp. 60-78

Author(s):

Shaobin Lv ◽

Guoqiang Chen ◽

Jun Dai

Keyword(s):

Particle Swarm Optimization ◽

Pid Controller ◽

Ride Comfort ◽

Control Strategies ◽

Particle Swarm ◽

Active Suspension ◽

Fuzzy Pid ◽

Swarm Optimization ◽

Fuzzy Pid Controller ◽

Suspension Control

Background: The active suspension can be adjusted in real time according to the change of road condition and vehicle state to enhance the performance of active suspension that has received widespread attention. Suspension control strategies and actuators are the key issues of the active suspension, and are the main research directions for active suspension patents. Objective: The numerical analysis method is proposed to study the performance characteristics of the active suspension controlled by different controllers. Methods: The active suspension control model and control strategy based on particle swarm optimization are established, and two active suspensions controlled by the sliding mode controller and the fuzzy PID controller are proposed. Moreover, two active suspension systems are optimized by particle swarm optimization. Results: The results of the analysis show that the performance of the active suspension is significantly improved compared with the passive suspension when the vehicle runs on the same road. The ride comfort of the active suspension controlled by the fuzzy PID controller has the best adaptive performance when the vehicle runs on different grade roads or white noise roads. The active suspension controlled by the fuzzy PID controller has the best ride comfort. Conclusion: A good control strategy can effectively improve the performance of the active suspension. To improve the performance of the active suspension, it can be controlled by utilizing different control strategies. The results lay a foundation for the active suspension experiments, the dynamic analysis and the optimization design of suspension structure.

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Online Adaptive Neuro-Fuzzy Based Full Car Suspension Control Strategy

Handbook of Research on Novel Soft Computing Intelligent Algorithms - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-4450-2.ch021 ◽

2014 ◽

pp. 617-666 ◽

Cited By ~ 1

Author(s):

Laiq Khan ◽

Shahid Qamar

Keyword(s):

Degrees Of Freedom ◽

Ride Comfort ◽

Sliding Mode ◽

Active Suspension ◽

Suspension System ◽

Car Model ◽

Car Suspension ◽

Neuro Fuzzy ◽

Suspension Control ◽

Soft Computing Technique

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Performance analysis of MR damper based semi-active suspension system using optimally tuned controllers

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/09544070211004467 ◽

2021 ◽

pp. 095440702110044

Author(s):

Gurubasavaraju Tharehalli mata ◽

Vijay Mokenapalli ◽

Hemanth Krishna

Keyword(s):

Pid Controller ◽

Ride Comfort ◽

Sliding Mode ◽

Dynamic Performance ◽

Parametric Method ◽

Mr Damper ◽

Active Suspension ◽

Suspension System ◽

Sliding Mode Controller ◽

Road Excitation

This study assesses the dynamic performance of the semi-active quarter car vehicle under random road conditions through a new approach. The monotube MR damper is modelled using non-parametric method based on the dynamic characteristics obtained from the experiments. This model is used as the variable damper in a semi-active suspension. In order to control the vibration caused under random road excitation, an optimal sliding mode controller (SMC) is utilised. Particle swarm optimisation (PSO) is coupled to identify the parameters of the SMC. Three optimal criteria are used for determining the best sliding mode controller parameters which are later used in estimating the ride comfort and road handling of a semi-active suspension system. A comparison between the SMC, Skyhook, Ground hook and PID controller suggests that the optimal parameters with SMC have better controllability than the PID controller. SMC has also provided better controllability than the PID controller at higher road roughness.

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