Design of a denoising hybrid fuzzy-pid controller for active suspension systems of heavy vehicles based on model adaptive wheelbase preview strategy

Active suspension is an effective approach to improve vehicle performance, and it is of great importance to attenuate the vibration of the rear part of heavy vehicles with freight. This paper proposes a new hybrid fuzzy proportional-integral-derivative (PID) controller with model adaptive wheelbase preview and wavelet denoising filter in an active suspension system for heavy vehicles with freight. A half vehicle model is first built, followed with the construction of the road excitation profiles of the shock and vibration pavement. After the design and implementation of the control method, four performance indices of the vehicle are evaluated. To verify the effectiveness of the proposed method, the control performance of the integrated controller and the separate function of every single controller are evaluated respectively. Numerical results show that the integrated control algorithm is superior to the single controllers and is effective in improving the vehicle performance as compared with other methods. Moreover, the wavelet denoising filter is shown to be an effective way to improve the vehicle performance and enable the stability of the system against noise

Design an intelligent controller for full vehicle nonlinear active suspension systems

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 (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function

Development of Mathematical Models, Simulating Vibration Control of Tracked Vehicle Weapon Dynamics

Focuses upon development of the mathematical model, simulating the tracked vehicle weapon dynamics, integrated over a half car platform. Governing differential equations have been formulated for the weapon system using state space approach, simulating the elevation dynamics over a half vehicle chassis, and coded using Matlab. The elevation model of the weapon comprises 3 degrees of freedom, arising from the rotational dynamics of the drive, breech and muzzle, which has sequentially been coupled to the half car model. Thereafter, the backstepping, LQR and PID control techniques have been derived and incorporated into the state space matrix for the coupled dynamics model, in which the control parameters have been arrived at through various iterations. Comparative weapon dynamics response studies have been carried out between that obtained from the above control strategies and the passive model, over standard terrain conditions at specified speeds. The above study would form a very useful framework for implementation of alternate control strategies for weapon stabilisation in the full tracked vehicle

Quarter and Full Car Models Optimisation of Passive and Active Suspension System Using Genetic Algorithm

© The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/This study evaluates a suspension design of a passenger car to obtain maximum rider's comfort when the vehicle is subjected to different road profile or road surface condition. The challenge will be on finding a balance between the rider's comfort and vehicle handling to optimize design parameters. The study uses a simple passive suspension system and an active suspension model integrated with a pneumatic actuator controlled by proportional integral derivative (PID) controller in both quarter car and full car models having a different degree of freedoms (DOF) and increasing degrees of complexities. The quarter car considered as a 2-DOF model, while the full car model is a 7-DOF model. The design process set to optimise the spring stiffnesses, damping coefficients and actuator PID controller gains. For optimisation, the research featured genetic algorithm optimisation technique to obtain a balanced response of the vehicle as evaluated from the displacement, velocity and acceleration of sprung and unsprung masses along with different human comfort and vehicle performance criteria. The results revealed that the active suspension system with optimised spring stiffness, damping coefficients and PID gains demonstrated the superior riding comfort and road holding compared to a passive suspension system.Peer reviewe

Robust vehicle suspension system by converting active and passive control of a vehicle to semi-active control ystem analytically

This research article deals with a simplified translational model of an automotive suspension system which is constructed by considering the translation motion of one wheel of a car. Passive Vehicle Suspension System is converted into Semi Active Vehicle System. Major advantage achieved by this system is that it adjusts the damping of the suspension system without the application of any actuator by using MATLAB® simulations. The semi-active control is found to control the vibration of suspension system very well

Performance investigation of integrated model of quarter car semi-active seat suspension with human model

In this paper, an integrated model of a semi-active seat suspension with a human model over a quarter is presented. The proposed eight-degrees of freedom (8-DOF) integrated model consists of 2-DOF for the quarter car model, 2-DOF for the semi-active seat suspension and 4-DOF for the human model. A magneto-rheological (MR) damper is implemented for the seat suspension. The fuzzy logic-based self-tuning (FLST) proportional–integral–derivative (PID) controller allows to regulate the controlled force on the basis of sprung mass velocity error and its derivative as input. The controlled force is tracked by the Heaviside step function which determines the supply voltage for the MR damper. The performance of the proposed integrated model is analysed, in-terms of human head accelerations, for several road profiles and at different speeds. The performance of the semi-active seat suspension is compared with the traditional passive seat suspension to validate the effectiveness of the proposed integrated model with a semi-active seat suspension. The simulation results show that the semi-active seat suspension improves the ride comfort significantly by reducing the head acceleration effectively compared to the passive seat suspension

Design and implementation of hybrid vehicle using control of DC electric motor

The electric motors and its control technology are key components of hybrid electric vehicles (HEVs). Control of the electric motor is a fundamental issue for traction application in electric vehicles and HEVs. This paper presents the design, development and implementation of a hybrid vehicle using both an electric motor and petrol engine to increase efficiency and decrease carbon footprint. Initially, a prototype of a HEV is designed and the performance values are calculated, before a control system is developed and implemented to control the DC motor speed using a microcontroller as the vehicle’s electronic control unit along with simple proportional integral derivative (PID) control using speed as a feedback mechanism. The prototype made incorporated voltage, current, speed and torque sensors for feedback resulting in a closed loop control system which successfully matched the speed input of a user-controlled pedal sensor. A user interface was developed to show the driver of the vehicle key variables such as the revolutions per minute (RPM) of the motor, the speed of the vehicle along with the current being drawn, and the voltage applied to the motor with overall power. To output a variable voltage from the Arduino, a digital output was used with pulse width modulation (PWM) capabilities in order to provide a variable DC voltage to the speed controller

Multi-objective optimization of active suspension predictive control based on improved PSO algorithm

The design and control for active suspension is of great significance for improving the vehicle performance, which requires considering simultaneously three indexes including ride comfort, packaging requirements and road adaptability. To find optimal suspension parameters and provide a better tradeoff among these three performances, this paper presents a novel multi-objective particle swarm optimization (MPSO) algorithm for the suspension design. The mathematical model of quarter-car suspension is first established, and it integrates the hydraulic servo actuator model. Further a model predictive controller is designed for the suspension by using the control strategies of multi-step forecast, rolling optimization and online correction of predictive control theory. To use vehicle body acceleration, tire deflection and suspension stroke to represent the above three performances respectively, a multi-objective optimization model is constructed to optimize the suspension stiffness and damping coefficients. The MPSO algorithm includes extra crossover operations, which are applied to find the Pareto optimal set. The rule to update the Pareto pool is that the newly selected solutions must have two better performances compared with at least one already existed in the Pareto pool, which ensures that each solution is non-dominated within the Pareto set. Finally, numerical simulations on a vehicle-type example are done under B-level road surface excitation. Simulation results show that the optimized suspension can effectively reduce the vertical vibrations and improve the road adaptability. The model predictive controller also shows high robustness with vehicle under null load, half load and full load. Therefore, the proposed MPSO algorithm provides a new valuable reference for the multi-objective optimization of active suspension control

An investigation into the roll control of vehicles with hydraulically interconnected suspensions

University of Technology Sydney. Faculty of Engineering and Information Technology.This thesis presents the investigation into a roll-plane hydraulically interconnected suspension (HIS), which is safety-oriented and designed for the vehicle with a high centre of gravity (CG) and a low rollover threshold. As a potential replacement of anti-roll bars, the HIS possesses the ability to resist the roll motion of the vehicle body during cornering or sharp turning by improving the vehicle roll stiffness. The previous research has concluded that the HIS is superior to the anti-roll bars in terms of the anti-roll performance, but its road holding performance has not been thoroughly studied. In this research, the modelling, modal analysis and simulations are conducted to compare the road holding ability of the HIS and anti-roll bars. A multi-function HIS test rig is developed and mounted on a typical Sports Utility Vehicle (SUV). The related experiments are implemented on a four-post test rig. Both the simulation and experiment results confirmed that the HIS is better than anti-roll bars from the perspective of the road holding performance. To overcome the drawback of the HIS that it is unable to handle the large roll motion and the vehicle roll caused by uneven roads, the HIS is then developed to be actively controlled by a control unit. Only one servo valve is included in the control unit of the active HIS so that the system’s cost and energy consumption are much lower in comparison with the conventional active suspensions with four independent motor-actuators. An output feedback H∞ controller is developed based on an empirically estimated active HIS model at a half-car level. The active HIS controlled by the designed H∞ controller is experimentally validated on the test rig with considerable roll angle reductions. For further verifying the controllability of the active HIS and also comparing the effect of different categories of control methods on the active HIS, other three representative control algorithms are also applied to the active HIS equipped vehicle. They are the classic control methods: proportional-integral-derivative (PID) control, the optimal control algorithm: linear-quadratic regulator (LQR) control and the intelligent control algorithm: fuzzy logic control. The obtained fuzzy, fuzzy-PID and LQR controllers are implemented in simulations. The experiments of the fuzzy and fuzzy-PID controllers are also conducted. The fuzzy-PID controller presents the most promising and stable control performance among these three controllers. After that, an attempt is made to improve the control performance of the model-based controllers to enhance the roll resistance ability of the active HIS further. A nine-degrees-of-freedom (nine-DOF) model that can capture the physical characteristics of the active HIS more accurately is developed. The new system model that addresses the relation between the flow change and pressure variation of the hydraulic system, and the viscous resistance of the fluid is also included. Then an H∞ controller and an LQR controller are designed based on the new model and validated in simulations. The experiment of the H∞ controller is also performed on the test rig and the H∞ controller derived from the new model is compared with the H∞ controller derived from the old model. The results show that the H∞ controller based on the new model improves the control performance slightly. Lastly, an effort is made to reduce the effects of the time delay caused by the fluid system by considering the system time delay when developing the controller. Delay-independent and delay-dependent H∞ state feedback controllers are designed and applied to the half car model. The simulation validations of the obtained controllers are carried out in MATLAB. It is found that the developed delay-dependent H∞ controller can provide stable and acceptably good control performance even with system time delay

Design and Evaluation of an Optimal Fuzzy PID Controller for an Active Vehicle Suspension System

The goal of studying the vehicle suspension systems is to reduce the vehicle vibrations which are due to the irregularities of road levels and the fluctuations in the vehicle velocity. These vibrations are transferred to the body and occupants of vehicles through the suspension system. In general, the main function of an active suspension system is to support the vehicle body by reducing the input vibrations and to provide a safe and smooth ride on a bumpy road surface. In this research, a quarter vehicle model has been employed for designing a suspension system. The road level irregularities have been considered as disturbances to this system. The optimal fuzzy PID (OFPD+I) controller has been used to optimize the performance of the suspension system in reducing the adverse effects resulting from road level irregularities, vehicle braking, and moving around the road curves. To verify the efficacy of the optimal fuzzy PID controller, its performance has been evaluated and compared with the performances of three separate controllers (PID, fuzzy, and fuzzy PID) and a system without any controller. The findings indicate the advantage of the optimal fuzzy PID controller over the other systems. Thus, in the integral of the absolute error criterion for the vehicle body velocity and displacement changes, the OFPD+I controller has a superior performance relative to the other systems