Managing the handling–comfort contradiction of a quarter-car system using Kalman filter

2021 ◽  
pp. 014233122199495
Author(s):  
Alhelou Muhammed ◽  
Alexander Gavrilov
Keyword(s):  
Kalman Filter ◽  
Time Constant ◽  
Control Unit ◽  
Active Suspension ◽  
Suspension System ◽  
Driving Safety ◽  
Unit Design ◽  
Dual Estimation ◽  
Active Design ◽  
Vehicle Suspension System

This article introduces a new approach to manage the “handling–comfort” contradiction of a vehicle suspension system. The idea is based on determining a specific time constant that reflects the percentage of suspension damping. This time constant is defined using the measurement of the sprung mass acceleration and the suspension deflection. A distinction is made between the control unit design for a semi-active suspension system and the control unit design for an active suspension system. The semi-active design is based on two sensors and a Kalman filter (KF), while the active design is based on three sensors and a dual-estimation KF. For active suspension, a third sensor was added to measure the acceleration of the unsprung mass. Simulation is carried out in Simulink and Simscape environments. The results of the proposed approach were compared with the results achieved by the hybrid-hook system. Simulation results showed a better efficiency of the proposed approach in driving safety during a “comfort” situation.

Extended Kalman Filter for Vehicle Suspension System

2014 ◽  
Vol 573 ◽  
pp. 317-321 ◽  
Author(s):  
K. Rajeswari ◽  
Anjali
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Ride Comfort ◽  
Active Suspension ◽  
Measurement Model ◽  
Suspension System ◽  
Vertical Acceleration ◽  
Hydraulic Actuator ◽  
Actuator Dynamics ◽  
Vehicle Suspension System

This paper presents an estimator for a nonlinear active suspension system considering the hydraulic actuator dynamics. PID controller is used to control the Active suspension system of nonlinear quarter car model. Extended Kalman filter is designed to estimate the states from the measurement model perturbed with noise. Simulation results demonstrate the effectiveness of the PID based active suspension system in reducing the vertical acceleration transmitted to the passengers thereby improving the ride comfort. Also the effectiveness of the Extended Kalman filter in estimating the actual vehicle states is demonstrated.

Design of Vehicle Semi-Active Suspension System Control Unit

2012 ◽  
Vol 220-223 ◽  
pp. 1995-1999
Author(s):  
Hong Kun Zhang ◽  
Wen Jun Li
Keyword(s):  
Embedded System ◽  
Control Strategy ◽  
Ride Comfort ◽  
Integrated Control ◽  
Control Unit ◽  
Active Suspension ◽  
Suspension System ◽  
System Control ◽  
Control Effect ◽  
Minimax Strategies

This paper researches on embedded system design based on MC9s12Dp256 microcontroller for vehicle semi-active suspension. The hardware design of suspension control unit (SCU) is introduced. The integrated control strategy which integrates Skyhook and MiniMax strategies is proposed. The hardware-in-the-loop simulation (HILS) test on a two-degree-of-freedom quarter car semi-active suspension system model is carried out. The functions of SUC are verified and the performance of passive suspension and semi-active suspension is compared. The simulation results indicate that the performance of SCU achieves design requirement. In comparison with passive system, the control effect of integrated control strategy can be improved in ride comfort and drive safety.

Optimized Fractional-Order Proportional Integral Derivative Controller for Active Vehicle Suspension System Performance Enhancement

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
A.S. Emam ◽  
H. Metered ◽  
A.M. Abdel Ghany
Keyword(s):  
Fractional Order ◽  
Performance Enhancement ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Vehicle Stability ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Vehicle Suspension System

In this paper, an optimal Fractional Order Proportional Integral Derivative (FOPID) controller is applied in vehicle active suspension system to improve the ride comfort and vehicle stability without consideration of the actuator. The optimal values of the five gains of FOPID controller to minimize the objective function are tuned using a Multi-Objective Genetic Algorithm (MOGA). A half vehicle suspension system is modelled mathematically as 6 degrees-of-freedom mechanical system and then simulated using Matlab/Simulink software. The performance of the active suspension with FOPID controller is compared with passive suspension system under bump road excitation to show the efficiency of the proposed controller. The simulation results show that the active suspension system using the FOPID controller can offer a significant enhancement of ride comfort and vehicle stability.

scholarly journals Design of LQG Controller for Active Suspension without Considering Road Input Signals

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Hui Pang ◽  
Ying Chen ◽  
JiaNan Chen ◽  
Xue Liu
Keyword(s):  
Angular Acceleration ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Body ◽  
Vehicle Suspension ◽  
Linear Quadratic ◽  
The Road ◽  
Input Signals ◽  
Vehicle Suspension System ◽  
Weight Coefficients

As the road conditions are completely unknown in the design of a suspension controller, an improved linear quadratic and Gaussian distributed (LQG) controller is proposed for active suspension system without considering road input signals. The main purpose is to optimize the vehicle body acceleration, pitching angular acceleration, displacement of suspension system, and tire dynamic deflection comprehensively. Meanwhile, it will extend the applicability of the LQG controller. Firstly, the half-vehicle and road input mathematical models of an active suspension system are established, with the weight coefficients of each evaluating indicator optimized by using genetic algorithm (GA). Then, a simulation model is built in Matlab/Simulink environment. Finally, a comparison of simulation is conducted to illustrate that the proposed LQG controller can obtain the better comprehensive performance of vehicle suspension system and improve riding comfort and handling safety compared to the conventional one.

scholarly journals Adaptive Neuro Fuzzy Inference Controller for Full Vehicle Nonlinear Active Suspension Systems

2010 ◽  
Vol 6 (2) ◽  
pp. 97-106
Author(s):  
A. Aldair ◽  
W. J. Wang
Keyword(s):  
Fuzzy Inference ◽  
Active Suspension ◽  
Suspension System ◽  
The Body ◽  
Full Vehicle ◽  
Road Roughness ◽  
Neuro Fuzzy ◽  
Control Forces ◽  
Vehicle Suspension System ◽  
The Cost

The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order PIλDμ (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function.

scholarly journals Performance Comparison of Various controllers on Semi-Active Vehicle Suspension System

2021 ◽  
Vol 40 ◽  
pp. 01001
Author(s):  
Sarvesh Walavalkar ◽  
Viraj Tandel ◽  
Rahul Sunil Thakur ◽  
V.V Pramod Kumar ◽  
Supriya Bhuran
Keyword(s):  
Active Suspension ◽  
Suspension System ◽  
Internal Model Control ◽  
Vehicle Body ◽  
Vehicle Suspension ◽  
Inference System ◽  
Proportional Integral ◽  
Suspension Systems ◽  
Model Control ◽  
Vehicle Suspension System

The value of a self-tuning adaptive semi-active control scheme for automotive suspension systems is discussed in this paper. The current vehicle suspension system uses fixed-coeffcient springs and dampers. The ability of vehicle suspension systems to provide good road handling and improve passenger comfort is usually valued. Passive suspension allows you to choose between these two options. Semi-Active suspension(SAS), on the other hand, can provide both road handling and comfort by manipulating the suspension force actuators directly. The semi-active suspension system for a quarter car model is compared to passive and various controllers such as Proportional-Integral, Proportional-Integral-Derivative, Internal model control (IMC)-PID, IMC-PID with filter, FUZZY, and Adaptive-network-based fuzzy inference system(ANFIS) in this analysis. This research could be relevant in the future for designing better car suspension adjustments to eliminate vertical jerks and rolling motion experienced by the vehicle body on bumps and humps.

A study of a Kalman filter active vehicle suspension system using correlation of front and rear wheel road inputs

2000 ◽  
Vol 214 (5) ◽  
pp. 493-502 ◽  
Author(s):  
F Yu ◽  
J-W Zhang ◽  
D. A. Crolla
Keyword(s):  
Kalman Filter ◽  
Rear Wheel ◽  
Suspension System ◽  
Estimation Accuracy ◽  
Vehicle Suspension ◽  
Vehicle Speed ◽  
State Variables ◽  
Performance Improvements ◽  
Vehicle Suspension System ◽  
Active Vehicle Suspension System

Based on a half-vehicle model, an algorithm is proposed for a Kalman filter optimal active vehicle suspension system using the correlation between front and rear wheel road inputs. In this paper, two main issues were investigated, i.e. the estimation accuracy of the Kalman filter for state variables, and the potential improvements from wheelbase preview. Simulations showed good estimations from the state observer. However, if the wheelbase preview algorithm is incorporated, the estimation accuracy for the additional states significantly decreases as vehicle speed and the corresponding measurement noises increase. Significant benefits from wheelbase preview were further proved, and the available performance improvements of the rear wheel station could be up to 35 per cent. Because of the feasibility and effectiveness of the proposed algorithm, and no additional cost for measurements and sensing needs, wheelbase preview can be a promising algorithm for Kalman filter active suspension system designs.

scholarly journals Multiobjective Optimization of Nonlinear Active Suspension System with Time-Delayed Feedback

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Su-Juan Shao ◽  
Dong Jing ◽  
Chuan-Bo Ren
Keyword(s):  
Time Delay ◽  
Multiobjective Optimization ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Function Optimization ◽  
Driving Safety ◽  
Optimal Time ◽  
Feedback Parameter ◽  
The Stability

Considering the nonlinear properties of spring and damping of suspension, a quarter-car model with time-delayed control is established. The Routh–Hurwitz stability criterion and stability switching method are used to analyze the stability of the system and obtain the stability region diagram. The multiobjective optimization function is established by considering the ride comfort, driving safety, and handling stability. The optimal control parameters are obtained by the optimization and simulation of the system under harmonic excitation and random excitation. In addition, the responses of the active suspension system with optimal time-delay control and the passive suspension system without control are compared. The results show that the active suspension system with time-delay displacement feedback control can reduce the vibration of the system, and there is an optimal feedback parameter combination to optimize the vehicle running state. The design of multiobjective function optimization proposed in this paper can improve ride comfort, driving safety, and handling stability and provide guidance for comprehensively improving vehicle performance.

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