Browse Topic: Semi-active suspension systems

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BO-NRPPO: A Bayesian Optimization–Tuned Proximal Policy Optimization Framework for Semi-Active Suspension Control10-10-03-00256/25/2026
Semi-active suspension systems enhance ride comfort and handling performance by adaptively modulating damping characteristics. However, conventional model-based controllers often fail to maintain optimal performance under uncertain and time-varying vehicle conditions. This article proposes Bayesian Optimization–Tuned Proximal Policy Optimization with Non-Parametric Rewards (BO-NRPPO), a novel reinforcement learning (RL) framework that integrates Bayesian Optimization (BO) with Proximal Policy Optimization (PPO) and a non-parametric reward function (NRF). The proposed approach enables adaptive self-tuning, data-driven reward shaping, and uncertainty-aware policy learning. Moreover, a Trapezoidal Simple Moving Average (TSMA)–based reward normalization scheme is introduced to accelerate convergence and stabilize training. Simulation results across diverse driving scenarios demonstrate that BO-NRPPO outperforms the passive suspension, the classical Linear Quadratic Regulator (LQR), and PPO with parametric rewards. Specifically, compared to the passive suspension and the LQR baseline, BO-NRPPO achieves up to 6.63% and 5.14% improvements in handling stability, respectively. Concurrently, it delivers maximum enhancements of 46.96% and 42.55% in ride comfort over these two baselines. For real-world vehicle applications, this adaptive self-tuning capability significantly reduces the time-consuming manual calibration efforts typically required in chassis development. Furthermore, Hardware-in-the-loop (HiL) validation confirms its real-time applicability and robustness under uncertain driving conditions, highlighting its immense potential as a scalable intelligent suspension control solution.
Chen, Guoying, Wang, Xinyu, Wang, Jiaqi, Zhan, Xinwang, Bi, Chenxiao, Cong, Shiqi, Hua, Min, Sun, Tianjun, Gao, Zhenhai
Multi-Mode Control Strategy for Controllable Vehicle Suspension Systems2026-99-07125/15/2026
The suspension system with variable damping and variable stiffness actuators can realize four-quadrant mechanical output, effectively combining the energy efficiency of the semi-active suspension with the performance levels approaching those of active suspensions. However, the practical effectiveness of this system depends heavily on the ability of the control strategy to adapt to different driving conditions. In order to meet this challenge, this research has developed a multi-mode suspension collaborative control strategy to optimize energy efficiency and ride comfort in various operating scenarios. Based on the four-quadrant characteristics of the actuator, a suspension mode switching framework has been established, and the suspension work is divided into passive, semi-active, pseudo-active and active modes. In order to determine the appropriate switching boundary, first calculate the root mean square (RMS) value of the sprung mass acceleration and suspension dynamic deflection under passive conditions. With the existing human comfort sensitivity as a reference, the switching threshold of sprung mass acceleration is 0.527 m/s2, and the switching threshold of suspension dynamic deflection is 8.31×10−3m, and the corresponding conversion rules are formulated. Then, the LQR controller optimized by the genetic algorithm is used to allocate the control force adaptively according to the suspension mode to realize cooperative multi-mode operation. The simulation results on B-D composite road surfaces show that compared with traditional passive suspension, this method can reduce the sprung mass acceleration, suspension dynamic deflection and tire dynamic load by 10.59%, 16.65% and 32.9% respectively. These results confirm that the collaborative control strategy significantly improves the ride comfort, vehicle adaptability and overall performance in complex road conditions.
Li, Zhiying, Li, Jei, Zhu, Anding, Bai, Xianxu, Li, Weihan, Li, Rui
Optimizing Ride Comfort and Stability in In-Wheel Motor Drive Electric Vehicles: A Correlated Semi-Active Suspension System with Kalman Filter and Spring-Type Analysis10-10-04-00304/24/2026
This research provides a unique contribution to the field of in-wheel motor drive (IWMD) electric vehicles (EVs) by addressing the challenges associated with the use of permanent magnet synchronous motors (PMSMs) for traction. These motors, integrated into the unsprung masses, increase the wheels’ rotational inertia, reducing ride smoothness on uneven roads. To mitigate this issue, we present an optimal Kalman filter for a magnetorheological (MR) control suspension system that correlates road inputs between the front and rear wheels. This filter significantly improves the estimation accuracy of state variables by incorporating the motor’s vertical motion, along with potential enhancements from wheelbase preview. To determine the most suitable coil spring types for use with MR dampers, we used the WDW-600 computer-controlled electronic universal testing machine to evaluate three coil spring types: constant-pitch (model A), variable-pitch (model B), and conical (model C). To assess the impact of controlled vibration on dynamic performance, we compared the dynamic characteristics of IWMD EVs equipped with passive, uncorrelated, and correlated suspension systems, all of which have controlled inverters integrated into their design. The results indicate that motor vertical acceleration and dynamic tire load are the primary factors influencing the dynamic behavior of EVs. Additionally, the vehicle’s vibration performance metrics are negatively impacted by the in-wheel motor driving system in both passive and uncorrelated suspension systems. However, the MR-controlled suspension system with a conical spring significantly enhances ride comfort and dynamic stability by addressing complex stiffness and evaluating the effects of different coil spring types on the structural response of EVs. This analysis is based on a correlated-suspension-system scenario.
Gad, Ahmed Shehata, Jabeen, Syeda Darakhshan, El-Zomor, Haytham M., Tolba, Mohamed, Elamy, Mamdouh I.
Ideal Skyhook-Groundhook Model Informed Wheelbase-Preview Controller for Semi-Active Suspension System2025-01-732512/31/2025
The suspension system, as a critical component of vehicle chassis, connects body frame and wheels, therefore affecting the ride comfort and handing stability of vehicles. To prevent high-frequency oscillations from large control increments of traditional algorithms, an ideal reference model is introduced to ensure a more smooth and efficient suspension responses that align with actual physical characteristics. The ideal skyhook, ideal groundhook, and ideal skyhook-groundhook models are evaluated with respect to their frequency response. As a result, the optimal configuration-ideal skyhook-groundhook model, exhibits the best overall performance and is incorporated with wheelbase preview mechanism as reference model (WP-SHGH). Further, a wheelbase-preview controller based on MPC framework (WPMPC-SHGH) is developed to regulate the responses of semi-active suspension. The Adams/Car-Simulink co-simulation platform is built for validation and comparison on the impact and ISO-B random roads. Compared to the passive suspension and the similar controller without reference model, the proposed WPMPC-SHGH significantly reduces vertical acceleration and pitch acceleration of vehicle body, which thereby enhances vehicle ride comfort. In addition, while maintaining suspension performances, the WPMPC-SHGH anticipates less control forces and leads to a reduction in energy consumption of semi-active suspension.
Yang, Li, Wang, Qingyun, Tan, Kanlun, Chen, Hao, Zhang, Zhifei
Integral–Derivative-Tilted Controller for Semi-Active Magnetorheological Truck Suspension System Using Combined Multi-Objective Ant Colony Optimization Algorithm02-19-02-000910/29/2025
This study proposes a novel control strategy for a semi-active truck suspension system using an integral–derivative-tilted (ID-T) controller, developed as a modification of the TID controller. The ant colony optimization (ACO) algorithm is employed to tune the controller parameters. Performance is evaluated on an eight-degrees-of-freedom semi-active suspension system equipped with MR dampers. The objective is to minimize essential dynamic responses (displacement, velocity, and acceleration) of the sprung mass, cabin, and seat. The controller also considers the nonlinear effects including suspension travel, pitch dynamics, dynamic tire loads, and seat-level vibration dose value (VDV). System performance is assessed under both single bump and random road excitations. The ACO-tuned ID-T controller is compared against passive suspension, MR passive (OFF/ON), and ACO-tuned PID and TID controllers. Simulation results demonstrate that the proposed controller achieves superior performance in both time and frequency domains under diverse road conditions.
Gad, S., Metered, H., Bassiuny, A. M.
Developing Military Light Utility Vehicle Performance Based on Air Semi-Active Suspension System Using Recurrent Neural Network–Based Controller10-09-04-00306/19/2025
This research presents a semi-active suspension system that combines an air spring and a magneto-rheological (MR) fluid damper to produce both active force and variable damping rates based on the road conditions. The suspension system used for the military light utility vehicle (MLUV) has seven degrees of freedom. A nonlinear model predictive control system generates the desired active force for the air spring control signal, while the linear quadratic regulator (LQR) estimates the target tracking of the intended damping force. The recurrent neural network is designed to develop a controller for an identification system. To achieve the optimal voltage for the MR damper without log time, it is used to simultaneously determine the active control force of the air spring by modifying the necessary damping force tracking. The MLUV suspension system is integrated with the traction control system to improve overall vehicle stability. A fuzzy traction controller adjusts the throttle angle based on the driver’s throttle input and the slip ratio of the driving wheels. Constant speed, passing maneuvers, increasing acceleration, and forceful braking are the four scenarios the driver uses to assess the traction control capability. Investigations are conducted to examine the interaction between the suspension and traction systems and how this interaction influences the integrated model that represents the vehicle’s behavior and performance. The effectiveness of the suspension is assessed under bump and random road excitations, based on the presentation of vehicle performance criteria in both the time and frequency domains. The results of the simulation show that in terms of ride comfort and vehicle stability, the air–MR suspension system performs significantly better than the passive suspension system. A fuzzy traction controller can smooth out the torque applied to the vehicle’s wheels by adjusting the engine’s speed and torque.
Shehata Gad, Ahmed
A Study on Luxury Captain Seat Vibration in MPV Vehicles with Semi-Active Suspension2025-01-01075/5/2025
More and more captain-seat-like, luxury individual seats have been appeared inside MPV vehicles in order to meet various customer needs and improve market competitiveness. In the same time, customer complaints about seat vibration also increase significantly. Thus, luxury captain seat vibration is becoming MPV issues facing the vehicle development engineers. Typically, luxury captain seats are much heavier due to the added mechanisms to provide functions like massage or temperature controls, etc., and it is not feasible to structurally improve the seat modal frequencies to meet the need for NVH issue resolution. This paper presents a systematical study on the second-row luxury captain seat vibration issue between 10-25Hz with MPV vehicles. An axle contribution is analyzed with a 4-poster shaker test, and the test data show that the seat vibration is more sensitive to rear axle excitation than that of front axle, and to the out-of-phase excitation than the in-phase one. The similar results are displayed by a coherence analysis of on-road test data. It also discusses the effects of a continuous damping control (CDC) shock absorber and air spring tuning on the seat vibration, and the engineering resolutions for the development of the suspension, body and seat. The CDC current effect on seat vibration is interpreted through a quarter-car suspension model in theory.
Zhou, Changshui, Yu Sr, Jing, Gu, Perry, Zhang, Fan, Bu, Kunquan, Liu, Xinhua
On-the-Market Air Suspension Systems for Passenger Cars10-09-02-00164/28/2025
This article conducts a thorough review of contemporary air suspension systems on the market for passenger cars. The evolution of suspension structures and control methodologies are briefly discussed. The layout of air suspension systems is introduced in detail, with each component receiving a comprehensive description and analysis. The open-loop and closed-loop arrangements are explained. Various types of air springs are discussed and compared. The sensory system, special working conditions, and failure analysis are also elaborated. In the case studies, some example models are listed to show a complete guide of how air suspension is implemented on passenger cars, which includes functionalities, air spring configurations, control methods, signal flow, service modes, and diagnostic messages. The major sources are OEMs’ official websites and previously released documents, such as user manuals and maintenance manuals, which are valid up to April 2023. Finally, the article concludes with a forward-looking discussion on the future application of air suspension.
Ma, Changye, Lu, Yukun, Zhen, Ran, Liu, Yegang, Pan, Bingwei, Khajepour, Amir
Active Suspension System Optimal Control Strategy Considering Vehicle Ride Comfort and Road Maintenance Capability2025-01-82774/1/2025
The suspension system could transmit and filter the forces between the body and road surface, which affects vehicle ride comfort and road maintenance capability. Compared to traditional passive and semi-active suspension, Active Suspension Systems (ASS) could automatically adjust the suspension stiffness, damping force, and body height according to changes in the vehicle's load distribution, travelling speed, and braking action through the addition of a power source such as a linear motor. Although the existing advanced control methods could help to effectively improve the driving quality of vehicles equipped with ASS, the conflict between ride comfort and road maintenance capacity is still a difficult problem to be solved. Therefore, an Active Suspension System optimal control strategy considering vehicle ride comfort and road maintenance capability is proposed in this paper. Firstly, a quarter ASS model and a road model are respectively developed based on the system dynamics relationship and the stochastic sinusoidal superposition method. Then, the model predictive control theory is applied to establish the execution force optimal controller of ASS, which takes into account the Sprung Mass Acceleration (SMA), Suspension Working Space (SWS), Dynamic Tire Deformation (DTD), actuator constraints, and control consumption. Thirdly, Improved Sparrow Search Algorithm (ISSA) Combining Cauchy Mutation and Opposition-Based Learning is designed to tune the built-in parameters of the ASS execution force optimal controller. Simulation results show that the control strategy proposed in this paper could help to maintain good ride comfort and road maintenance capability for vehicles fitted with ASS under various road conditions.
Zhu, Bing, Zhang, Chaohui, Sun, Jihang, Wang, Shiwei, Ding, Shuwei, Li, Lun, Chen, Zhicheng
Artificial Intelligence Technique Applied to Semi-Active Vibration Control in Vehicle Suspension System2025-01-82704/1/2025
This study investigates the influence of magnetorheological (MR) dampers in semi-active suspension systems (SASSs) on ride comfort, vehicle stability, and overall performance. Semi-active suspension systems achieve greater flexibility and efficacy by combining MR dampers with the advantages of active and passive suspension systems. The study aims to measure the benefits of MR dampers in improving ride comfort, vehicle stability, and overall system performance. The dynamic system model meets all required performance criteria. This study demonstrates that the proposed artificial intelligence approach, including a fuzzy neural networks proportional-integral-derivative (FNN-PID) controller, significantly enhances key performance criteria when tested under various road profiles. The control performance requirements in engineering systems are evaluated in the frequency and time domains. A quarter-car model with two degrees of freedom (2 DOF) was simulated using MATLAB/Simulink to assess the suggested controller’s performance. The enhanced FNN-PID controller greatly increases ride comfort and vehicle stability when compared to fuzzy neural networks based on PID control strategies proposed, passive suspension systems, uncontrolled MR suspension, and PID controller, according to analysis of the simulated preliminary data. The algorithms' performance is evaluated using a wide range of crucial performance criteria, such as the suspension working space, body mass acceleration, dynamic tire load, and desired force. The phase plane method is used to evaluate system stability. The results clearly show that the proposed controller for the SASS significantly enhances both road holding and ride comfort, highlighting its strong potential for real-world applications.
M.Faragallah, Mohamed, Metered, Hassan, Abdelghany, M.A., Essam, Mahmoud A.
Vibration Mitigation of Semi-Active Vehicle Suspension System Incorporating Magnetorheological Damper Using Hybrid Control2025-01-82694/1/2025
Magnetorheological (MR) dampers, known for their remarkable dependability and cost-effectiveness, have established themselves as prime semi-active vibration control devices in engineering systems. MR dampers are categorized as adaptive devices because their features may be readily adjusted by applying a regulated voltage signal. Their ability to offer superior performance while mitigating the drawbacks of fully active actuators underscores their practical significance. This research is to investigate some system hybrid controllers using a combination state derivative feedback and a linear-quadratic regulator for use in conjunction with the damper controller of a semi-active suspension of a Quarter vehicle model to improve ride comfort and vehicle stability. The mathematical model of 3 degrees of freedom for semi-active suspension using MR dampers will be derived and simulated using MATLAB and SIMULINK software. In order to quantify the effectiveness of the suggested control strategies, the control performance criteria will be assessed in both the time domain and the frequency domain engineering systems. Initial findings demonstrate an improvement in the semi-active system, which compared with the passive suspension system without any control system and the semi-active suspension system with a classical PID controller.
M.Faragallah, Mohamed, Metered, Hassan, Essam, Mahmoud A.
Design Optimization of Electro-Hydraulic Valve Performance Through Simulation and Experimental Methods2025-01-86424/1/2025
The main purpose of the semi-active hydraulic damper (SAHD) is for optimizing vehicle control to improve safety, comfort, and dynamics without compromising the ride or handling characteristics. The SAHD is equipped with a fast-reacting electro-hydraulic valve to achieve the real time adjustment of damping force. The electro-hydraulic valve discussed in this paper is based on a valve concept called “Pilot Control Valve (PCV)”. One of the methods for desired force characteristics is achieved by tuning the hydraulic area of the PCV. This paper describes a novel development of PCV for practical semi-active suspension system. The geometrical feature of the PCV in the damper (valve face area) is a main contributor to the resistance offered by the damper. The hydraulic force acting on the PCV significantly impacts the overall performance of SAHD. To quantify the reaction force of the valve before and after optimization under different valve displacements and hydraulic pressures were simulated using comprehensive three-dimensional (3D) Computational Fluid Dynamics (CFD) methods. For computational model validation purposes, PCV prototypes of the optimized design were procured and tested on a suitable test rig to obtain the hydraulic damping force characteristics at different input current signals. The proposed virtual development method using CFD simulation allows early selection of semi-active valve before physical prototype build. The performance characteristics of a prototype derived from the optimal design of the SAHD assembly are presented. The simulation and experimental results show an improvement in the semi-active damping force under certain conditions. This capability is crucial for systems like SAHD, where rapid and precise control of oil flow is essential.
Chintala, Paramesh, Hornby, Ryan
Enhancing Vehicle Safety: Investigating the Role of Active Anti-Roll Bars in Vehicle Dynamics2024-36-005812/20/2024
A serious problem of public healthcare around the world is the number of road vehicle accidents, every year almost 1,3 million people die and approximately 20 to 50 million people suffer a non-fatal accident because of a road vehicle accident [1]. As a result of that, in 2021 the World Health Organization stated the “The Second Decade of Action for Road Safety”, which the goal is to prevent at least 50% of deaths and injuries due traffic by 2030. To achieve this goal, the automobile companies have invested in technology and products that can enhance vehicle safety. Despite exist some control systems able to reduce roll, and consequently the roll over, such as active suspension, semi-active suspension, and stability control systems, none of them have as main purpose reduce the number of rollovers. The following study aims to examine the effects of an active anti roll bar, to improve the vehicle dynamics during corners and reduce the risk of a rollover by reducing the roll of the sprung mass and reducing the total weight transfer of the vehicle. The model utilized to reproduce the vehicle dynamics was a bicycle model with 3 degrees of freedom, to describe the tyre lateral forces it was used the nonlinear Pacejka model and as actuator to the active anti roll bar was modeled a direct current motor. The study of cases has shown that during a fishhook maneuver the active anti roll bar was able to improve the performance of the vehicle by reducing the roll angle during the transient and steady state.
Gomes, Pedro Carvalho, Teixeira, Evandro Leonardo Silva, Morais, Marcus Vinicius Girão, Fortaleza, Eugenio Liborio Feitora, Santos Gioria, Gustavo
Semi-Active Suspension Design for Truck Using Pneumatic Spring Joining MR Fluid Damper Based on Neural Networks Controller10-09-01-000110/21/2024
In order to modify both stiffness and damping rates according to various road conditions, this research introduces a pneumatic spring in conjunction with a magnetorheological (MR) fluid damper as a single suspension unit for each wheel in the truck. Preventing weight transfer and improving riding comfort during braking, acceleration, and trajectory prediction are the main objectives. A two-axle truck has been used, consisting of three degrees of freedom for the sprung mass, including vertical, pitch, and roll motions, and four degrees of freedom for the unsprung masses, which have been redesigned according to the different types of springs and dampers. Pneumatic-controlled springs, often referred to as dynamic or classic models, replace laminated leaf springs commonly found in vehicles. Additionally, an MR damper replaces a hydraulic double-acting telescopic shock absorber. These models are studied to evaluate the effect of pneumatic spring parameters on truck dynamics. Pneumatic stiffness and the intended damping force are monitored by a recurrent neural network in conjunction with leveling control. This process provides the recommended voltage for the MR damper based on the Signum function damper controller. The performance of the suspension is assessed in the time and frequency domains for both step and random road excitations using vehicle dynamic parameters. Six suspension system configurations are compared with the air spring dynamic model integrated with the MR damper (Model 6), which is recommended as a suspension system for trucks. According to simulation data, when compared to alternative suspension systems, Model 6 significantly enhances both ride comfort and vehicle stability. Model 6 offers improvements in tire workload, truck path, tire–ground contact point during acceleration, braking efficiency, and stopping distance. Compared to previous controlled models, Model 6 also demonstrates zero steady-state offset and zero steady-state error.
Shehata Gad, Ahmed, El-Zomor, Haytham M.
Discretization-Based Semi-Active Suspension Control Using Road Preview Data2024-01-50878/30/2024
While semi-active suspensions help improve the ride comfort and road-holding capacity of the vehicle, they tend to be reactive and thus leave a lot of room for improvement. Incorporating road preview data allows these suspensions to become more proactive rather than reactive and helps achieve a higher level of performance. A lot of preview-based control algorithms in literature tend to require high computational effort to arrive at the optimal parameters thus making it difficult to implement in real time. Other algorithms tend to be based upon lookup tables, which classify the road input into different categories and hence lose their effectiveness when mixed types of road profiles are encountered that are difficult to classify. Thus, a novel MPC (model predictive control)-based algorithm is developed which is easy to implement online and more responsive to the varying road profiles that are encountered by the vehicle. The efficacy of the algorithm is tested against a numerical methods-based control algorithm that can determine the maximum possible ride comfort achieved using semi-active dampers capable of altering their damping characteristics every 0.01 s. Results indicated that the proposed strategy is quite effective in providing holistic improvement in the sprung mass motion, achieving on average 69% of the maximum ride comfort possible with a fraction of the computational effort.
Thamarai Kannan, Harish Kumar, Ferris, John B.
Control Strategy of Semi-Active Suspension Based on Road Roughness Identification10-08-02-00134/13/2024
Taking the semi-active suspension system as the research object, the forward model and inverse model of a continuous damping control (CDC) damper are established based on the characteristic test of the CDC damper. A multi-mode semi-active suspension controller is designed to meet the diverse requirements of vehicle performance under different road conditions. The controller parameters of each mode are determined using a genetic algorithm. In order to achieve automatic switching of the controller modes under different road conditions, a method is proposed to identify the road roughness based on the sprung mass acceleration. The average of the ratio between the squared sprung mass acceleration and the vehicle speed within a specific time window is taken as the identification indicator for road roughness. Simulation results show that the proposed road roughness identification method can accurately identify smooth roads (Class A–B), slightly rough roads (Class C), and severely rough roads (Class D–H). The designed multi-mode semi-active suspension controller automatically adapts to the identified road roughness, resulting in improved ride comfort on severely rough roads and improved handling performance on smooth roads. Finally, a real vehicle test is performed. The test results show that the proposed road roughness identification method can effectively distinguish between a well-paved roads and rough roads. In addition, the ride comfort of the vehicle is significantly improved in the comfort mode of the controller on rough roads.
Feng, Jieyin, Yin, Zhihong, Xia, Zhao, Wang, Weiwei, Shangguan, Wen-Bin, Rakheja, Subhash
Design and Development of Base Valve for a Semi-Active Damper2024-01-25934/9/2024
A semi-active suspension system provides superior safety, ride, and handling performance for a vehicle by continuously varying the damping based on vehicle motions, where semi-active hydraulic damper (SAHD) is the most critical component. Today, SAHD’s are standard in most of the premium segments of vehicles and optional extras in mid-size and compact vehicle segments. Electric vehicles require larger sized SAHD’s to meet heavier vehicle loads and meet ride and handling requirements. The aim of this paper is to highlight the design and development methodology of a base valve for larger bore-size for semi-active hydraulic damper. The workflow follows to present a process for base valve design to meet structural strength and, the key steps of design calculations of the hydraulic performance. The design of the base valve and suction disks architecture was engineered with the aid of Computer Aided simulations. The structural performance was analyzed using the Finite Element Analysis (FEA) and valve hydraulic performance factors were obtained by using Computational Fluid Dynamics (CFD) methods to simulate the physics of hydraulic fluid flow around the base valve assembly using the de-coupled fluid /structure interaction (FSI) method. In this effort, the analytical study was reinforced to identify the critical performance parameters such hydraulic pressure (P) - oil discharge (Q) curve generation and understand the base valve design performance. Furthermore, valve characterization using flow bench testing was conducted to validate and correlate the simulation predictions with prototype samples to increase the confidence level in computer aided simulations.
Chintala, Paramesh, Patwa, Aakash, Sankaran, Shivanand
Control Strategy for Semi-Active Suspension Based on Suspension Parameter Estimation2024-01-27714/9/2024
This paper presents an adaptive H2/H∞ control strategy for a semi-active suspension system with unknown suspension parameters. The proposed strategy takes into account the damping force characteristics of continuous damping control (CDC) damper. Initially, the external characteristics of CDC damper were measured, and a forward model and a back propagation (BP) neural network inverse model of CDC damper were proposed using the measured data. Subsequently, a seven-degree-of-freedom vehicle with semi-active suspension system and H2/H∞ controller was designed. Multiple feedback control matrices corresponding to different sprung mass parameter values were determined by analyzing time and frequency domain performance. Finally, a dual observer system combining suspension state and parameter estimation based on the Kalman filter algorithm was established. The estimated parameter was used to determine feedback control matrix, while the observed states were used to calculate the desired damping force of CDC damper. Simulation results show that the proposed adaptive H2/H∞ control strategy can estimate sprung mass value in real time, enabling the switching of feedback control matrix based on the estimated results. Consequently, vehicle ride comfort is enhanced while handling stability is not excessively deteriorated. Compared to real-time calculation of control parameters method, the proposed control strategy reduces computations and ensures robustness of semi-active suspension systems.
Du, Canjie, Yin, Zhihong, Xia, Zhao, Wang, Weiwei, Shangguan, Wen-Bin
Modelling, Simulation and Testing of Adaptive Sliding Mode Control for Semi-Active Suspension System Based on Road Information2024-01-27654/9/2024
The accuracy of chassis control for intelligent electric vehicles (IEVs), especially in road-based IEVs control for improving road holding and ride comfort, is a challenging task for the intelligent transport system. Due to the high fatality rate caused by inaccurate road-based control algorithms, how to precisely and effectively choose a reasonable road-based control algorithm become a hot topic in both academia and industry. To address and improve the performance of road holding and ride comfort of IEVs by using a semi-active suspension system, an adaptive sliding mode control (ASMC) algorithm-based road information is proposed to realize the overall performance of the intelligent vehicle chassis system in the paper. Firstly, the models of road excitation and equivalent hybrid control of a quarter semi-active suspension system are established. Secondly, connecting with the minimum redundancy maximum relevance (MRMR) approach and probability neural network (PNN) theory, the method of road classification is developed based on the MRMR-PNN algorithm under various road excitation. Thirdly, using the sliding mode variable structure and neural network control theory, an ASMC algorithm based road information is developed. Then, a cuckoo search-based multi-objective optimization method is employed to obtain the optimization control parameters of the proposed ASMC algorithm. Finally, compared with the passive suspension system, the skyhook control algorithm, and the ASMC algorithm by simulation and test, the performance indexes of road holding and ride comfort are analyzed under ISO-C road excitation. Simulation and experimental results show that the better performance of the proposed ASMC algorithm can be obtained under different control weights of semi-active suspension system performance indexes, but also the root mean square values of sprung mass acceleration and rattle space compared with passive suspension system optimize no less than 6%. The research achievements develop a reasonable algorithm to apply to improving chassis performance for electric vehicles.
Wang, Zhenfeng, Liao, Yinsheng, Zhang, Zhijie, Hu, Zhiming, Zhao, Gaoming, Huang, Taishuo, Zhang, Lei
Damping Force Optimal Control Strategy for Semi-Active Suspension System2024-01-22864/9/2024
Semi-active suspension system (SASS) could enhance the ride comfort of the vehicle across different operating conditions through adjusting damping characteristics. However, current SASS are often calibrated based on engineering experience when selecting parameters for its controller, which complicates the achievement of optimal performance and leads to a decline in ride comfort for the vehicle being controlled. Linear quadratic constrained optimal control is a crucial tool for enhancing the performance of semi-active suspensions. It considers various performance objectives, such as ride comfort, handling stability, and driving safety. This study presents a control strategy for determining optimal damping force in SASS to enhance driving comfort. First, we analyze the working principle of the SASS and construct a seven-degree-of-freedom model. Next, the damping force optimal control strategy is designed by comprising of the Genetic Algorithm (GA) and the Linear Quadratic Regulator (LQR). The cost function, which provides a quantitative evaluation of the controlled vehicle's driving comfort performance, is constructed by calculating the root mean square value of the body's vertical acceleration, suspension dynamic deflection, and wheel dynamic deformation. Based on this evaluation, we utilize the LQR to convert the damping force control problem of the SASS into a multi-objective optimal control problem. At the same time, the GA is used to comprehensively optimize weighted coefficients of the cost function, and successfully achieve the damping force optimal control for SASS. Finally, we constructed a joint simulation platform using CarSim and MATLAB/Simulink to evaluate and validate. The simulation results demonstrate the SASS’ optimal damping force control strategy could considerably enhance the vehicle ride comfort under various operating conditions comparing with the passive suspension.
Zhao, Jian, Li, Wanting, Zhu, Bing, Chen, Zhicheng, Ding, Shuwei, Li, Junwei, Hao, Wenquan, Zhang, Yong
Evaluation of Semi-Active Vehicle Suspension System Performance Incorporating Magnetorheological Damper Using Optimized Feedback Controller Based on State-Derivative2024-01-22884/9/2024
The purpose of this paper is to investigate the efficiency of a quarter car semi-active suspension system with the state-derivative feedback controller using the Bouc-Wen model for magneto-rheological fluids. The magnetorheological (MR) dampers are classified as adaptive devices because of their characteristics can be easily modified by applying a controlled voltage signal. Semi-active suspension with MR dampers combines the benefits of active and passive suspension systems. The dynamic system captures the basic performance of the suspension, including seat travel distance, body acceleration, passenger acceleration, suspension travel distance, dynamic tire deflection and damping force. With minimal reliance on the use of sensors, the investigation aims to improve ride comfort and vehicle stability. In this study, the state derivative feedback controller and Genetic algorithm (GA) is utilized to improve the performance of semi-active suspension system. Moreover, the cost is reduced compared to the passive suspension and the active suspension systems in which sensors and actuators are used. The performance of the semi-active suspension is represented by applying the road profile to the system. This is accomplished by simulating and analyzing system performance using MATLAB and SIMULINK. Initial results show an improvement in the semi-active system, which includes both the passive suspension system without any control system and the active suspension system with a PID controller.
M.Faragallah, Mohamed, Metered, Hassan, Abdelaziz, Taha H.
Vibration Control of MR-Damped Half Truck Suspension System Using Proportional Integral Derivative Controller Tuned by Ant Colony Optimization2024-01-22894/9/2024
Proportional integral derivative (PID) control technique is a famous and cost-effective control strategy, in real implementation, applied in various engineering applications. Also, the ant colony optimization (ACO) algorithm is extensively applied in various industrial problems. This paper addresses the usage of the ACO algorithm to tune the PID controller gains for a semi-active heavy vehicle suspension system integrated with cabin and seat. The magnetorheological (MR) damper is used in main suspension as a semi-active device to enhance the ride comfort and vehicle stability. The proposed semi-active suspension consists of a system controller that calculate the desired damping force using a PID controller tuned using ACO, and a continuous state damper controller that predict the input voltage that is required to track the desired damping force. The ACO algorithm is used to solve the nonlinear optimization problem to search the PID controller gains by finding the optimal problem solution. A mathematical model of an eight degree-of-freedom MR-damped heavy vehicle suspension system is derived and simulated using Matlab/Simulink software. The proposed ACO PID controlled suspension is compared to both MR semi active (ON-OFF) and conventional passive system. System performance criteria are evaluated under different road disturbances to quantify the success of the proposed controller. The simulated results reflect that the proposed ACO PID controller of the MR-damped heavy vehicle suspension offers a significant enhancement in ride comfort and vehicle stability.
Gad, Sherif, Metered, Hassan, Bassiuny, A. M., Abdel-Ghany, Abdel-Ghany
Ride Comfort Enhancement of Railway Vehicles Using Magnetorheological Damper2024-01-22914/9/2024
The study investigates the ride comfort of a rail vehicle with semi-active suspension control and its effect on train vertical dynamics. The Harmony Search algorithm optimizes the gains of a proportional integral derivative (PID) controller using the self-adaptive global best harmony search method (SGHS) due to its effectiveness in reducing the tuning time and offering the least objective function value. Magnetorheological (MR) dampers are highly valuable semi-active devices for vibration control applications rather than active actuators in terms of reliability and implementation cost. A quarter-rail vehicle model consisting of six degrees of freedom (6-DOF) is simulated using MATLAB/Simulink software to evaluate the proposed controller's effectiveness. The simulated results show that the optimized PID significantly improves ride comfort compared to passive.
Ali, Shaimaa A., Metered, Hassan, Bassiuny, A. M., Abdel-Ghany, A.M.
Adopting Pothole Mitigation System for Improved Ride, Handling and Enhanced Component Life2024-26-00591/16/2024
Potholes are a major cause of discomfort for riders and vehicle damage. The passive suspension systems which are used in the passenger vehicles are primarily reaction based. These can’t adapt to the changing road conditions which means the best ride quality and handling characteristics cannot be ensured for different driving situations. Passive suspension system also needs more maintenance due to its inability to reduce the impact of the road irregularities. In recent years, semi-active suspension systems have been developed to improve ride comfort and vehicle safety. This paper covers the integration of a semi-active suspension system with a road preview mechanism with a TATA car model to investigate its impact on ride comfort, handling characteristics and component loads in digital domain. A quarter car vehicle model is used to compare different active damping control strategies. The best strategy is selected and integrated in a full vehicle MBS model to gain deeper insight on ride and loadpaths. The simulation results show that the proposed system reduces the vertical acceleration and displacement of the vehicle during pothole impacts. The system also improved the vehicle's pitch, roll and other critical characteristics. Loads on different suspension components also reduced. Adoption of semi-active suspension systems in a TML passenger cars would lead to a transformation in the performance of ride comfort, handling dynamics and enhanced component life. The proposed system provides a practical and cost-effective solution to address the issue of potholes and has a positive impact on vehicle dynamics during pothole impacts. Overall, it will provide a more dynamic, comfortable and safer driving experience, making it a choice for a high performance car.
Mishra, Satyakam, Prasad, Tej, Maruenda Sanz, Javier
Damping Magnetorheological Systems Based on Optimal Neural Networks Preview Control Integrated with New Hybrid Fuzzy Controller to Improve Ride Comfort10-07-04-003210/3/2023
Adaptive neural networks (ANNs) have become famous for modeling and controlling dynamic systems. However, because of their failure to precisely reflect the intricate dynamics of the system, these have limited use in practical applications and perform poorly during training and testing. This research explores novel approaches to this issue, including modifying the simple neuron unit and developing a generalized neuron (GN). The revised version of the neuron unit helps to develop the system controller, which is responsible for providing the desired control signal based on the inputs received from the dynamic responses of the vehicle suspension system. The controller is then tested and evaluated based on the performance of the magnetorheological (MR) damper for the main suspension system. These results of the tests show that the optimal preview controller designed using the GN both ∑-Π-ANN and Π-∑-ANN can accurately capture the complex dynamics of the MR damper and improve their damping characteristics compared with other methods. The seat and main suspension systems work together to provide more support and comfort for the driver and passengers. The short stroke of the MR damper is used in seat suspension as it allows for more precise control over the suspension and can provide a smoother ride. The new hybrid fuzzy type-2 (T-2) control is designed to accurately estimate the desired damping force for the seat MR damper. This system also allows for the damping force to be adjusted to meet the desired requirements of the seat MR damper. This integration of damping systems allows better control and stability of the vehicle and provides a smoother ride for drivers and passengers. Furthermore, integrating the damping systems increases the overall performance of the vehicle, making it better able to handle various road conditions.
Shehata Gad, Ahmed, Darakhshan Jabeen, Syeda, Galal Ata, Wael
Interval Lower Singleton Fuzzy Optimal Controller Design of Magnetorheological Seat Suspension Integrated with Semi-Active Vehicle Suspension System2023-01-50669/22/2023
In this paper, semi-active MR main suspension system based on system controller design to minimize pitch motion linked with MR-controlled seat suspension by considering driver’s biodynamics is investigated. According to a fixed footprint tire model, the transmitted tire force is determined. The linear-quadratic Gaussian (LQG) system controller is able to enhance ride comfort by adjusting damping forces based on an evaluation of body vibration from the dynamic responses. The controlled damping forces are tracked by the signum function controllers to evaluate the supply voltages for the front and rear MR dampers. Based on the sprung mass acceleration level and its derivative as the inputs, the optimal type-2 (T-2) fuzzy seat system controller is designed to regulate the controlled seat MR damper force. The best rate for each linguistic variable is acquired by modifying the range between upper and lower membership functions (MFs), which enables accurate tracking of the seat-damping force. The parameters of the LQG main system controller and the ideal scaling lower ranges of the T-2 fuzzy seat system controller are both explored by a genetic algorithm (GA). The performance of LQG regulated for MR dampers is compared with that of linear-quadratic regulator (LQR) controlled for MR dampers and passive systems to measure the suspension efficacy under bump and random road disturbance. To verify the efficiency of the recommended integrated models on both the main and seat systems, the performance of the proposed ideal T-2 fuzzy-controlled MR semi-active seat suspension is compared with the passive seat suspension. The simulation results show that the LQG controlled connected with the T-2 fuzzy controlled can greatly improve both ride comfort and vehicle stability, among all examined systems.
Shehata Gad, Ahmed
Vibration Characteristics and Control Algorithms for Semi-Active Suspension of Space Exploration Vehicles2023-01-10645/8/2023
Suspension systems are an integral part of land vehicles and contribute significantly to the vehicle performance in terms of its ride comfort and road holding characteristics. In the case of Space Exploration Vehicles (SEVs), the requirement of these unmanned vehicles is to rove, collect pictures and transmit data back to the earth. This is generally performed with the help of exteroceptive, and proprioceptive sensors mounted on the main chassis of the SEV. The design of various components of such vehicles is dictated by the assumption of extreme terrain and environmental conditions that it might face. The Mars Exploration Rovers (MERs) have incorporated the use of the “Rocker-Bogie” mechanism for the suspension system which provides relative stability to the MER for various maneuvers. In this work, the “Rocker-Bogie” mechanism is modeled and simulated as a planar kinematic model using parameters of the Perseverance rover. It is found that the Rocker-Bogie tends to nullify the effects of uneven terrain by maintaining the chassis at a relatively fixed location with respect to the ground reference frame. Further, an attempt is made to replace the mechanism with a passive and semi-active suspension module at four corner wheels to study the effects that the semi-active suspension would have on the chassis dynamics of the MER. Lastly, a comparative analysis of the vertical acceleration of the chassis using different suspensions was performed. This concluded that the rocker-bogie mechanism does help to stabilize the chassis dynamic behavior to a greater extent. Future work could include an attempt to utilize the rocker-bogie chassis dynamics as the ideal condition to develop control strategies that can improve the chassis dynamics if individual semi-active suspension systems were employed.
Shenvi, Mohit, Gorantiwar, Anish, Sandu, Corina, Taheri, Saied
Optimal Damping Matching of Semi-Active Air Suspension Based on Vehicle Comfort and Handling2023-01-07814/11/2023
Many vehicles have been equipped with air springs as elastic elements to get better performance in comfort, but absorbers may not work in an optimal state due to the variation of suspension stiffness. While the function of semi-active suspension is to enable the absorber damping to be adjusted according to different road roughness levels and to coordinate between comfort and handling. To solve the problem of matching the damping coefficient of variable stiffness suspensions represented by air springs, this paper proposed a method for calculating the optimal damping ratio of a semi-active suspension system in real-time with sprung mass acceleration and dynamic tire load to establish the objective function and suspension dynamic deflection as the constraint to reflect the unification of comfort and handling. The effectiveness of the proposed damping calculated method is validated by comparing it with classical methods including passive suspension and shy-hook control on straight roads with different road roughness.
Zhu, Qingxiao, Chen, Zixuan, Yu, Dong, Lao, Zhenhai, Zhang, Yunqing
Road Parameter Estimation with Drone-Vehicle Communication2023-01-06644/11/2023
The presented study is dedicated to the technology supporting vehicle state estimation and motion control with a concept drone, which helps the vehicle in sensing the surroundings and driving conditions. This concept allows also extending the functionality of the sensors mounted on the vehicle by replacing or including additional parameter observation channels. The paper discusses the feasibility of such a drone-vehicle interaction as well as demonstrates several design configurations. In this regard, the paper presents a general description of the proposed drone system that assists the vehicle and describes an experiment in measuring the profile of the road with a range sensor. The results obtained in the experiment are described in terms of the accuracy to be achieved using the drone and are compared with other studies, which use the methods of estimation from the sensors mounted on the vehicle. The proposed measurement concept can be applied to a large number of vehicle systems such as adaptive cruise control, active or semi-active suspension, and wheel slip control. The road profile is captured in real-time by a drone, and the telemetry data is processed by the host computer.
Beliautsou, Viktar, Beliautsou, Aleksandra, Ivanov, Valentin
Switchable Control Strategy Study of a Novel Multi-function Electromagnetic Damper Based on Road Classification2023-01-01734/11/2023
Electromagnetic damper (EMD), which has shown good vibration isolation and energy harvesting potential, has received much attention in recent years. In addition, the harvested energy of EMD systems can be used to further suppress severe vibration. When the harvested energy of the suspension system is more than the consumed energy, the suspension system can realize self-powered functions. However, the integration of the above three functions is a challenge for the design of EMD systems. In this paper, a novel multi-function electromagnetic damper (MFEMD) system, which integrates the semi-active vibration control mode, energy-harvesting mode, and self-powered mode, is introduced first. The MFEIS system applies an H-bridge circuit to control the multi-directional flow of circuit energy flow, and the supercapacitor is used as the energy storage device because of its high-power density and rapid response speed. Since vehicles are driving in complex road conditions in the real world, road information needs to be considered to control the MFEMD system. Additionally, the energy recovery efficiency and vibration suppression performance of the MFEMD system also need to be balanced. A switchable control strategy based on road classification is proposed to switch the state of the MFEMD system. According to the real driving conditions, roads are classified into three categories, namely high-speed smooth roads, medium-speed good roads, and low-speed bad roads. The state of the MFEMD system is switched based on the road information to balance the ride comfort and energy recovery efficiency. A complex road, which contains different levels of random roads, is adopted to verify the effectiveness of the proposed control strategy. Simulation results verified the effectiveness of the proposed switchable control strategy compared with a well-tuned passive suspension and a semi-active suspension.
Xia, Xiangjun, Ning, Donghong, Liao, Yulin, Liu, Pengfei, Du, Haiping
VTR 4 X 4 THREE-DIMENSIONAL MATHEMATICAL MODEL WITH INDEPENDENT SUSPENSIONS AND MAGNETORREOLOGICAL DAMPERS2022-36-00362/10/2023
A vehicle must be designed in such a way that it guarantees its occupants safety and comfort in the face of various situations, such as a sudden lane change, something that can happen at any time during a trip or even a military operation. In this situation, the car must react to this excitement without compromising the car's stability. In this context, the present work aims to study the application of semi active suspension with magnetorheological dampers assisted by an embedded electronics system in order to improve the dynamic behavior of the vehicle, whose suspension springs are modeled in a non-linearly way using polynomials. To this end, this study performs an analysis of the vertical and lateral dynamics of a 4 x 4 vehicle with 10 degrees of freedom. The model construction uses the power flow methodology to establish the relationship between the kinematics and the dynamics of the chassis. The computational implementation was made utilizing block diagram methodology, using one commercial software.
dos Santos Belle, Vilson Wenis, da Costa Neto, Ricardo Teixeira
Four-Wheel Vehicle Response under Bump, Pothole, Harmonic, and Random Excitations Using Bond Graph/Simulink Technique02-16-02-000811/10/2022
The present article analyses a 7 degrees of freedom full car model of a light four-wheel wheeler formulated analytically and using the bond graph/Simulink technique. A full car model formulated using the Bond graph/Simulink technique is fed with the bump, pothole, harmonic, and random excitations to analyze the vehicle’s dynamic behavior. The bond graph/Simulink model is validated by comparing its results with that of the analytical model when subjected to circular bump inputs and comparing its results with that of the field test when subjected to random inputs. The vehicle model is fitted with a skyhook control strategy on the axles and the response of the semi-active system is compared with the passive system. The present analysis suggests that a vehicle system with semi-active suspension shows improved vibration isolation characteristics as compared with passive suspension system when subjected to different types of excitations.
Sharma, Rakesh Chandmal, Palli, Srihari, Gopala Rao, L. V. V., Duppala, Azad, Sharma, Sunil Kumar
Letter from the Special Issue Editors10-06-04-002211/4/2022
Letter from the Special Issue Editors
Kaldas, Mina, Trimboli, Sergio, Recker, Darrel, Hoersken, Christian
Initial Pitch Control for Semi-active Suspension System10-06-04-00278/18/2022
The aim of this study is to develop an Add-On Feature that could support the semi-active suspension system controller during longitudinal dynamics maneuvers. The Add-On Feature called Initial Pitch Control (IPC) is activated during launching, shifting, and braking to enhance the pitch motion characteristics and road-holding capability. A sixteen degrees-of-freedom (DoF) vehicle mathematical model represents the vertical and longitudinal dynamics developed and validated via laboratory and road tests. A hydraulic four-poster test rig is used to carry out the laboratory tests for the vertical dynamics verification, while the longitudinal dynamic verification is achieved through the performed tests on a highway track. In order to design the IPC algorithm, the Rule-Optimized (RO) semi-active suspension controller, an Anti-lock Braking System (ABS) controller, and seven gears Dual-Clutch Transmission (DCT) controller are implemented in the vehicle model. An optimization routine has been applied to find the optimum force gains for the IPC algorithm. The IPC algorithm is evaluated in terms of the body pitching motion and the road holding during launching and braking. Comparisons between the passive suspension and semi-active suspension systems with and without the proposed IPC algorithm have been performed. The obtained results illustrated that the IPC algorithm with the semi-active controller improved both the pitching motion and road-holding characteristics of the vehicle compared with the passive suspension system and semi-active suspension without IPC.
Kaldas, Mina M., Rivas, Jorge, Soliman, Aref M.A.
Development of a Driver-in-the-Loop Simulation to Evaluate the Performance to Energy Trade-Off of Active Dynamics Systems on an Electric Race Car2022-01-50405/30/2022
Automotive industry interest in renewable propulsion technology has led to a surge of investment in electric-only motorsport categories as a technological test bed. Electrification has enabled easier implementation of active vehicle dynamics control systems to improve performance and drivability, but limitations in battery technology create significant constraints which force a compromise between efficiency and performance. In this paper, four different control systems—Automatic Rear Steering (ARS), Drag Reduction System (DRS), Semi-Active Suspension (SAS), and Torque Vectoring (TV)—are tested in various configurations and combinations with the aim of characterizing their performance to energy consumption trade-offs in an electric Formula Student vehicle. A Driver-in-the-Loop (DiL) simulator was developed using Cruden Panthera along with a multibody Simulink vehicle model to capture the effects of drivability on vehicle performance. Vehicle configurations were tested using a combination of open-loop and closed-loop driving maneuvers, measuring performance indicators to capture absolute performance, power consumption, and driver workload. TV was the most effective at improving vehicle performance but also incurred the largest energy cost. ARS was also found to improve performance by a lesser degree but brought the greatest improvement to drivability. DRS improved straight-line performance and energy consumption at the expense of cornering performance and driver workload. SAS improved steady-state cornering performance but had minimal effect on transient maneuvers to justify its energy cost and complexity. Using TV, DRS, and ARS in conjunction was found to be the optimal configuration by quantifiably improving driver workload, lap time performance, and power consumption over the baseline vehicle.
Chrysakis, Georgios, Vogel, Jonathan, Nikzadfar, Kamyar
Semi-Active Control of ISD In-Wheel Motors Suspension with Dynamic Vibration Absorber2022-01-02853/29/2022
Electric vehicles driven by in-wheel-motor have the advantages of compact structure and high transmission efficiency, which is one of the most ideal energy-saving, environmentally friendly, and safe driving forms in the future. However, the addition of the in-wheel-motor significantly increases the unsprung mass of the vehicle, resulting in a decrease in the mass ratio of the vehicle body to the wheel, which will deteriorate the ride comfort and safety of the vehicle. To improve the vibration performance of in-wheel-motor driven vehicles, a semi-active inerter-spring-damper (ISD) suspension with in-wheel-motor (IWM) dynamic vibration absorber (DVA) of the electric wheel is proposed in this paper. Firstly, a structure of in-wheel-motor DVA is proposed, which converts the motor into a dynamic vibration absorber of the wheel to suppress the vibration of the unsprung mass. Secondly, based on a damper-inerter integrated device, a tandem ISD suspension was introduced into the electric vehicle. Then, an improved Sky-Hook (ISH) semi-active controller of ISD suspension is designed. Compared with the passive suspension, the semi-active ISD suspension with DVA proposed can significantly reduce the vibration of the vehicle body in a wide range of frequencies. Meanwhile, the road adhesion of the vehicle is also improved greatly. It can be concluded that the proposed semi-active suspension with DVA can effectively improve the ride comfort of the vehicle driven by in-wheel-motor.
Zhang, Kaidi, Wu, Jinglai, Zhang, Yunqing
Enhancement of Semi-active Vehicle Suspension System Performance Using Magnetorheological Damper2022-01-50183/11/2022
Vehicle suspension is considered a vital system of modern automotive and necessary to offer an adequate level of ride comfort and roadholding. In the present paper, a fuzzy-based sliding surface (FBSS) controller is designed, as a system controller for the first time, for a semi-active vehicle suspension using a magnetorheological (MR) damper in order to minimize the transmitted unwanted vibrations to the passengers. Therefore, an ideal reference skyhook model is employed to construct the sliding surface, which is the input of fuzzy logic. MR damper is a semi-active device and is controlled indirectly using an external voltage source. So a neural-based damper controller is used to compute the applied voltage to the magnet coil of the MR damper in series with the FBSS system controller. The proposed semi-active controlled quarter-vehicle suspension using an MR damper is solved numerically by Matlab. Simulation results are generated in time and frequency domains to judge the suspension system efficacy under different road profiles. Finally, the results indicated that the proposed semi-active MR suspension system controlled using FBSS offers an outstanding improvement of ride comfort and roadholding in comparison with the passive, uncontrolled MR and also controlled using linear-quadratic-regulator (LQR) suspension systems.
Metered, Hassan
Mathematical Model of the APC Guarani equipped with 30 mm Turret and Magnetorheological Dampers2021-36-00962/4/2022
The combat cars design seeks to balance mobility and fire power, in order to enable the vehicle to shot with accuracy, although running on rough roads. The gun follows the chassis movement, as well as the cannon shots produce forces that change the car dynamics. Because of that, the suspension system of military vehicles has not only to reduce the oscillations caused by the terrain but also has to damper the gun recoil after each shot, preventing misalignment between the tube and the target. Therefore, the present study goal is to evaluate how semiactive dampers could reduce the chassis pitch motion of the Armored Personnel Carrier 6x6 Guarani, from the Brazilian Army, equipped with magnetorheological dampers, while running on a rough road and shooting with the 30 mm cannon at the same time. The proposed model uses the power flow concept to establish the kinematics relationships of the vehicle subsystems, and thus determinate the causality relationships among the components. It is considered the MacPherson setup and the hypothesis that the suspension springs are non-linear. Besides that, the magnetorheological damper is controlled by a system that uses fuzzy logic. The computational implementation was developed in MATLAB software Simulink in order to reproduce the three-axle vehicle model using block diagram. Finally, the results shows that the semi-active suspension helps to reduce the chassis response against obstacles and forces due the cannon shots, besides to improve the ride comfort.
da Costa Neto, Ricardo Teixeira, Souza, Rogério Felipe Alberto
Model Reference Adaptive Control of Semi-active Suspension Model Based on AdaBoost Algorithm for Rollover Prediction10-06-01-000511/9/2021
Due to their large volume structure, when a heavy vehicle encounters sudden road conditions, emergency turns, or lane changes, it is very easy for vehicle rollover accidents to occur; however, well-designed suspension systems can greatly reduce vehicle rollover occurrence. In this article, a novel semi-active suspension adaptive control based on AdaBoost algorithm is proposed to effectively improve the vehicle rollover stability under dangerous working conditions. This research first established a vehicle rollover warning model based on the AdaBoost algorithm. Meanwhile, the approximate skyhook damping suspension model is established as the reference model of the semi-active suspension. Furthermore, the model reference adaptive control (MRAC) system is established based on Lyapunov stability theory, and the adaptive controller is designed. Finally, on the same road condition, the rollover warning control simulations are carried out under the following conditions: the 180-degree step, the fishhook, and the double-lane-change condition. Simulation results show that the proposed reference adaptive control based on the AdaBoost algorithm for rollover control can effectively predict vehicle rollover in early warning and improve the anti-rollover capability of vehicles.
Tianjun, Zhu, Wan, Hegao, Wang, Zhenfeng, Wei, Ma, Xu, Xuejiao, Zhiliang, Zou, Sanmiao, Du
On the Road Profile Estimation from Vehicle Dynamics Measurements2021-01-11158/31/2021
Ride comfort assessment is undoubtedly related to the interaction between the vehicle tires and the road surface. Indeed, the road profile represents the typical input for tire vertical load estimation in durability analysis and for active/semi-active suspension controller design. However, the road profile evaluation through direct experimental measurements involves long test time and excessive cost required by professional instrumentations to detect the road irregularities with sufficient accuracy. An alternative is shifting attention towards efficient and robust algorithms for indirect road profile evaluation. The object of this work aims at providing road profile estimation starting from vehicle dynamics measurements, through accessible and traditional sensors, with the application of a linear Kalman filter algorithm. The filter is designed and tuned by considering the pitch/bounce half-car models for the prediction phase and by measuring vertical accelerations and angular speeds for the correction phase. The estimator is then tested on experimental data, acquired driving a passenger car over a road bump at different vehicle speeds. The vehicle used in the experimental campaign is a two-passenger electric quadricycle involved in the demonstration phase of the European project STEVE.
Vella, Angelo Domenico, Tota, Antonio, Vigliani, Alessandro
Energy Harvesting Application in an Automotive Suspension Using an Hybridised and Highly Miniaturised Generator (MFKI-HNG) - Low Invasiveness SystemSAE-PP-001658/9/2021
Energy regeneration systems in automotive suspensions are nowadays very impactful and often imply a redesign of the suspension system. The aim of this work is to propose and evaluate the applicability of a miniaturised and hybridised generator to power an inertial sensor and a microcontroller, in order to obtain an energy-independent and low-invasive sensor-generator-controller scheme that is also suitable for retrofitting. The proposed system was analysed from an electronic point of view and a possible application in a double whishbone suspension mechanism was presented. The results showed that it is possible to power the entire proposed system by means of a single generator, recovering approximately 3.6 W at 5 Hz, with a packaging volume of 26805 mm^3.
Paolucci, Federico, Oddo, Girolamo
A Preview Type-2 Fuzzy Controller Design for the Semi-active Suspension to Improve Adhesion Characteristics during Braking and Handling2021-01-50696/28/2021
A full vehicle of a preview control semi-active suspension system based on an interval type-2 fuzzy controller design using a magnetorheological (MR) damper to improve ride comfort is investigated in this paper. It is integrated with the force distribution system to obtain the optimal rate of road adhesion during braking and handling. The nonlinear suspension model is derived by considering vertical, pitch, and roll motions. The preview interval type-2 fuzzy technique is designed as a system controller, and it is attached with a Signum function method as a damper controller to turn on the voltage for the MR damper. This voltage is adjusted for each wheel based on the external excitation generated by road roughness in order to enhance ride comfort. To describe the effectiveness and adaptable responses of the preview controlled semi-active system, the performance is compared with both the passive and MR passive suspension systems during time and frequency domains. The mathematical models of full-vehicle suspension systems are solved using MATLAB/Simulink software. The Magic Formula tire model is used to evaluate both longitudinal and lateral forces based on normal load estimated by a suspension system. These forces are adjusted for each wheel based on the distribution control used in the braking system. Simulation results show that the novel semi-active controlled system integrated with the force distribution system used for the braking system can achieve ride comfort with the supporting contact patch significantly according to the investigated factors including tire workload, stopping braking distance, weight transfer, and cornering force.
Shehata Gad, Ahmed
Vertical and Longitudinal Coupling Control Approach for Semi-active Suspension System Using Mechanical Hardware-in-the-Loop Simulation10-05-02-00103/12/2021
When the vehicle is under braking condition in the longitudinal motion, the vehicle body will tilt due to the inertial force in motion. A high amplitude will result in uncomfortable feelings of the occupant, such as nervousness or dizziness. To solve the problem, this article presents an adaptive damping system (ADS), which combines the vehicle anti-pitch compensation control with the mixed skyhook (SH) and acceleration-driven-damper (ADD) control algorithm. This ADS can not only improve the vibration effect of the vertical motion for the vehicle but also consider the longitudinal motion of the vehicle body. In addition, a new damper mechanical hardware-in-the-loop test bench is built to verify the effectiveness of the algorithm. Compared with passive suspension, the vertical acceleration amplitude of the center of gravity (COG) of this algorithm can be decreased by 21.16% and 13.21% on average at different speeds on B-class road and C-class road, and the amplitude of pitch angle variation can be dropped by 28.82% on average at different decelerations with little change in the longitudinal acceleration of the COG. The waveform road is established to verify the effectiveness of the proposed algorithm for the vertical and longitudinal coupling motion. Compared with passive suspension and SH, the vertical acceleration amplitude of the COG can be reduced by 18.87% and 12.58% on average at different speeds on a waveform road, and the amplitude of vehicle pitch angle variation can also be decreased in different time periods under little difference for the longitudinal acceleration of the COG. The new test bench can verify the effectiveness of the control algorithm under the condition of no real vehicle, which enriches the test methods of algorithm development for a semi-active suspension vehicle and shortens the project development period.
Zhu, Yugang, Bian, Xueliang, Chen, Daliang, Su, Lili, Li, Fei, Shi, Yan, Jin, Tianshi
Ride Comfort Improvement with Preview Control Semi-active Suspension System Based on Supervised Deep Learning10-05-01-00032/4/2021
As known to all, it is a challenging task to solve the delay of a controllable suspension system under the transient road. Thus, how to effectively and low-costly acquire road information and choose the reasonable control algorithm remains a hot topic in both academia and industry. With the rapid development and extensive application of the advanced intelligent driving system, a large number of sensors, such as cameras, have been installed on the vehicle, and deep learning technology has also been widely used to identify lane recognition, traffic direction signal, and pedestrian detection, but rarely used in semi-active suspension control. To address the above issues, a novel skyhook preview control (SPC) approach, which combines supervised deep learning, is proposed in the article. Firstly, a full vehicle dynamics model for semi-active suspension is established. Secondly, supervised deep learning (YOLOv3) is adopted to identify the transient road to preview the semi-active suspension. Finally, by comparing the vehicle road test results of the SPC with that of the skyhook wheelbase preview controller (SWPC), the skyhook controller (SC), and the passive suspension (PS), it is concluded that the designed algorithm can effectively improve the ride comfort of the vehicle.
Zhu, Yugang, Bian, Xueliang, Su, Lili, Gu, Cansong, Wang, Zhenfeng, Shi, Chenlu
Effect of Semi-active Suspension Controller Design Using Magnetorheological Fluid Damper on Vehicle Traction Performance2020-01-510110/30/2020
In order to achieve the high capability of the ride comfort and regulating the tire slip ratio, a preview of a nonlinear semi-active vibration control suspension system using a magnetorheological (MR) fluid damper is integrated with traction control in this paper. A controlled semi-active suspension system, which consists of the system controller and damper controller, was used to develop ride comfort, while the traction controller is utilized to reduce a generated slip between the vehicle speed and rotational rate of the tire. Both Fractional-Order Filtered Proportional-Integral-Derivative ( P¯IλDμ) and Fuzzy Logic connected either series or parallel with P¯IλDμ are designed as various methodologies of a system controller to generate optimal tracking of the desired damping force. The signum function method is modified as a damper controller to calculate an applied input voltage to the MR damper coil based on both preview signals and the desired damping force tracking. The fuzzy self-organizing mechanism is utilized for designing the electronic control unit of a traction control system (TCS) to adapt the tire torque produced from the powertrain based on the ratio of tire brake torque and the normal tire torque generated by controlling the MR damper. Suspension dynamics criteria described by the two degrees-of-freedom (2-DOF) ride model are used to compare between the passive suspension system and four types of control techniques applied in the semi-active suspension system during both time and frequency domains. The simulation results show that the MR semi-active suspension system using optimal preview Fuzzy- P¯IλDμ controller synchronizing with a fuzzy self-organizing mechanism can achieve optimal capabilities for both ride comfort and traction stability.
Gad, Ahmed Shehata, Mohamed, Eid S., El-Demerdash, Samir M.
Preview Model Predictive Control Controller for Magnetorheological Damper of Semi-Active Suspension to Improve Both Ride and Handling10-04-03-00219/23/2020
This article presents a semi-active vibration control suspension system using a preview Model Predictive Control (MPC) linked with a magnetorheological (MR) damper to improve vehicle stability during handling dynamics, consequently confidently achieving both maneuverability and lateral dynamic motion. The mathematical model (4DOF) described by bounce and pitch motions for sprung mass and two bounce motions for the un-sprung masses, which consists of a preview half-vehicle suspension system and MR dampers at the front and rear axles, is derived. A nonpreview case of the linear quadratic regulator (LQR), a preview case of the LQR, and a preview case of the MPC as alternative methods are applied to design the system controller in combination with a signum function method as a damper controller for both the front and rear MR dampers. The vehicle handling model based on the look-ahead distance of the road, which includes yaw and lateral motions, is linked with the driver model. Magic Formula is used to describe the performance of nonlinearity tire models at the front and rear axles. Suspension systems, which are described either by the passive model or by MR semi-active suspension model, are integrated with the handling model to examine the influence of vertical vibration control on the vehicle lateral stability. The MR semi-active vehicle suspension based on the mentioned control strategies is compared with a passive suspension system under road bump and random road excitations to analyze the vehicle dynamics criteria during both time domain and frequency domain. Simulation results confirm that the case of a semi-active MR suspension system incorporating the preview case MPC controller can offer significant prosperity for both ride comfort and vehicle stability compared with other proposed cases of vibration control.
Shehata Gad, Ahmed
Investigating Performance of Quarter-Car Semi-Active Suspension with Skyhook, Fuzzy Logic, Adaptive Neuro-Fuzzy Inference System Control Strategies for ISO-Classified Road Disturbance2020-01-50404/14/2020
In this paper, a quarter-car suspension system has been investigated for the International Organization for Standardization (ISO)-classified road profile with various control strategies. The vehicle suspension system provides ride comfort and handling by reducing the transfer of road disturbances or irregular road profile to the passenger and cargo materials. The suspension also retains the road and tire contact, stabilizing the vehicle’s movements. A combination of fuzzy logic and neural network, i.e., adaptive neuro-fuzzy inference system (ANFIS), is deployed as a control strategy to control the quarter-car semi-active suspension model. Quarter-car suspension models with a passive control and semi-active controller with different control strategies, viz., Skyhook, Fuzzy Logic (FLC), and ANFIS, are designed and modeled in MATLAB/SIMULINK®. Numerical simulations were performed on developed quarter-car models for an ISO-classified road profile disturbance, and the performance was compared. With respect to the passive suspension system, there is better ride comfort performance (9.7%) with skyhook control, but a compromise in handling, while FLC achieves both ride comfort (4%) and handling (6.12%), reducing the trade-off between both performances. This suspension performance is better achieved by the ANFIS ride comfort (54.57%) and handling (20.57%) with respect to (wrt) the passive suspension system. The comparative implementation of the above control strategies concludes better suspension by the ANFIS of the vehicle to the ISO-classified road disturbance than those other control strategies.
Mulla, Ansar Allauddin, Unune, Deepak Rajendra
Vibration Control of Semi-Active Vehicle Suspension System Incorporating MR Damper Using Fuzzy Self-Tuning PID Approach2020-01-10824/14/2020
In this paper, a nonlinear semi-active vehicle suspension system using MR fluid dampers is investigated to enhance ride comfort and vehicle stability. Fuzzy logic and fuzzy self-tuning PID control techniques are applied as system controllers to compute desired front and rear damping forces in conjunction with a Signum function method damper controller to assess force track-ability of system controllers. The suggested fuzzy self-tuning PID operates fuzzy system as a PID gains tuner to mitigate the vehicle vibration levels and achieve excellent performance related to ride comfort and vehicle stability. The equations of motion of four-degrees-of-freedom semi-active half-vehicle suspension system incorporating MR dampers are derived and simulated using Matlab/Simulink software. Control performance criteria including bounce and pitch motions are evaluated in both time and frequency domains in order to quantify the effectiveness of proposed system controllers under bump and random road disturbances. Fuzzy self-tuning PID controller gives a better force tracking than fuzzy logic. The performance of both controlled semi-active suspension systems using MR dampers is compared with MR passive and conventional passive to show the efficiency of the proposed controlled suspension systems. The simulation results prove that the semi-active MR suspension system controlled using fuzzy self-tuning PID controller can offer significant improvements of ride comfort and vehicle stability among all investigated systems.
Gad, Ahmed Shehata, Oraby, W., Metered, H.
Integrated Model Predictive Control and Adaptive Unscented Kalman Filter for Semi-Active Suspension System Based on Road Classification2020-01-09994/14/2020
The accuracy of state estimation and optimal control for controllable suspension system is a challenging task for the vehicle suspension system under various road excitations. How to effectively acquire suspension states and choose the reasonable control algorithm become a hot topic in both academia and industry. Uncertainty is unavoidable for the suspension system, e.g., varying sprung or unsprung mass, suspension damping force or spring stiffness. To tackle the above problems, a novel observer-based control approach, which combines adaptive unscented Kalman filter (AUKF) observer and model predictive control (MPC), is proposed in the paper. A quarter semi-active suspension nonlinear model and road profile model are first established. Secondly, using the road classification identification method based on system response, an AUKF algorithm is employed to estimate accurately the state of suspension system. Due to the nonlinear of semi-active suspension damping force in the movement process, the methods of observer-based and model predictive control are used to design the optimal predictive controller under various road excitations. Finally, compared with passive suspension system, the constrained optimal control (COC) algorithm and the model predictive control (MPC) algorithm, the road handing and ride comfort indexes are analyzed. Simulation results show that the performance of the proposed model predictive control algorithm compared with passive mode for the semi-suspension system improves more than 10% under the same road excitation condition.
Wang, Zhenfeng, Xu, Shengjie, Li, Fei, Wang, Xinyu, Yang, Jiansen, Miao, Jing
Magnetorheological Semi-Active Anti-Roll Bar for Automobiles07-12-02-00073/11/2020
Aiming at improving safety (anti-roll performance) with consideration of ride comfort of vehicles during cornering and over road irregularities, magnetorheological (MR) fluid-based semi-active anti-roll bar is investigated in this article. The vehicle roll model with both roll stiffness and roll damping of the vehicle body influenced by the MR anti-roll bar is established to analyze the impact of the torsional stiffness and torsional damping. Combining with the Pareto front of the lateral load transfer ratio (LTR) of the front axle, the optimal roll stiffness and roll damping of a vehicle are determined, and correspondingly the torsional stiffness and torsional damping of the anti-roll bar are determined. And then the mathematical model and multibody dynamic model of the anti-roll bar are established, and the simulation of the MR semi-active anti-roll bar model is carried out via MATLAB/Simscape Multibody. CarSim vehicle model equipped with the MR anti-roll bar is built and a fuzzy controller is designed according to the roll angle and roll rate. Co-simulation based on CarSim and MATLAB/Simulink is conducted to analyze the impact of MR anti-roll bar on vehicle roll performance.
Tang, Chao, Bai, Xian-Xu, Xu, Shi-Xu
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