Browse Topic: Active suspension systems

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Comfort Study of Air Suspension System Based on MPC Control2026-99-01367/31/2026
Air springs are increasingly replacing traditional shock absorbers in vehicle suspension systems due to their superior mechanical properties, including adjustable stiffness, nonlinear characteristics, and excellent damping performance. To further explore the potential of air suspension in improving ride comfort, this paper focuses on air suspension. We first conducted mechanical characteristic experiments on air springs to obtain their stiffness and damping characteristics under different inflation pressures and excitation frequencies. These tests provide essential mechanical parameters for subsequent modeling and simulation. Based on the experimental data, a simplified 1/4 air suspension simulation model is constructed, taking into account the nonlinear stiffness and damping properties of the air springs. To simulate real-world driving conditions, a random road surface model is introduced as the excitation input. Simulation analysis is conducted to compare the air suspension system with the traditional passive suspension system. The results indicate that, compared to the passive suspension system, the air suspension system integrated with Model Predictive Control(MPC) significantly reduces key performance indicators, including suspension deflection, wheel dynamic load, and sprung mass vertical acceleration. This indicates that the suspension with model predictive control can effectively suppress vehicle vibrations, thereby enhancing ride comfort and driving stability. The results of this study provide an important basis for the optimal design of air suspension systems and have practical application value for improving the suspension performance of the vehicle.
Yin, Zhi
Modeling and Damping Optimization Design of Commercial Vehicle Cab Air Suspension System2026-99-18627/17/2026
Based on the theory of vehicle dynamics, this paper first constructs a dynamic model of the cab air suspension system, laying a core theoretical framework for subsequent optimization research. At the level of performance evaluation indicators, the root mean square (RMS) values of the cab’s vertical acceleration, roll acceleration, and pitch acceleration are selected as key parameters. On this basis, an objective function for the damping matching of the cab air suspension system is established, clarifying the optimization direction. Building on this objective function, the paper further takes into account the constraint conditions in the actual operation of the system, using the probability of the cab air suspension system hitting the limit stop as a constraint. Finally, a complete mathematical model for the damping matching of the cab air suspension system is formed, and a genetic algorithm is used to solve this model, ensuring the scientificity and feasibility of the optimization results. To verify the effectiveness of the established model and optimization method, this paper conducts verification based on the aforementioned dynamic simulation model of the cab air suspension system: the frame displacement signals collected under actual random road conditions are used as the model input, and the established mathematical method for damping matching is applied to carry out the optimal matching design of the damping parameters of the cab air suspension system. The simulation optimization results show that the performance of the optimized system is significantly improved: the RMS value of vertical acceleration is reduced by 5% compared with that before optimization, the RMS value of roll angular acceleration is reduced by 11.2%, and the RMS value of pitch angular acceleration is reduced by 4.7%. In conclusion, the method constructed in this paper can effectively improve a practical and feasible reference for the damping optimization design of the cab suspension system.
Li, Saisai, Yang, Chang, Guo, Ruiling, Zhang, Zhongyuan, Liang, Dong, Wu, Shiyu
A Novel Stiffness Prediction Model of Rolling Lobe Air Springs Considering Irregular Piston Contour Geometry: Development and Experimental Validation15-19-02-00065/18/2026
An accurate air spring model is essential for the design and optimization of air suspension systems to achieve superior performance. This article presents a novel stiffness model for a rolling lobe air spring (RLAS), formulated using stiffness characteristic parameters. Prediction models for these parameters, including effective area and its change rate, as well as effective volume and its change rate, are derived through geometric analysis, based on polynomial fitting of the irregular piston contour. The local contour cone angle of the piston is determined by differentiating the polynomial function, capturing the geometry-dependent variation across the profile. Additionally, a nonlinear hysteresis model for the rubber bellows is integrated, combining a Berg friction component and a Kelvin-Voigt fractional derivative viscoelastic model to represent the amplitude- and frequency-dependent behavior of the RLAS. The proposed model is parameterized through quasi-static and dynamic bench tests under varying amplitudes and frequencies and is validated against both experimental data and an existing modeling approach. Comparative results demonstrate that the proposed model effectively and accurately predicts the static and dynamic responses of the RLAS.
Xia, Xiaojun, Zhang, Hong, Zou, Yi, Ye, Lei, Lu, Yi, Chen, Rui, Zou, Hantong, Wang, Yang
Limit Stability Control for Corner Module Vehicles Based on Hierarchical Hybrid Game10-10-04-00325/18/2026
Corner module vehicles (CMVs) achieve the decoupling of driving, braking, steering, and suspension, significantly enhancing vehicle handling potential, but under extreme operating conditions, the interactions between actuators severely constrain the improvement of vehicle handling performance. In order to mitigate conflicts between subsystems and enhance vehicle handling stability, a hierarchical hybrid game–based limit stability control method for CMVs is proposed in this article. Taking into account the handling potential of subsystems under limit conditions, a Stackelberg leader–follower game is designed by first designating Direct Yaw moment Control (DYC) as the leader and Active Rear Steering (ARS) as the follower. Subsequently, the DYC–ARS and Active Suspension System (ASS) were constructed into a non-cooperative game system, and the Nash equilibrium solution was solved through iteration. The lower-level controllers, respectively, established a tire force distribution model that minimizes the overall tire utilization rate and an active suspension force distribution model that does not affect the vehicle’s pitch, in order to enhance the safety margin of the vehicle under extreme conditions. Finally, the Hardware-in-the-Loop test results proved the effectiveness of the proposed controller.
Peng, Jinxin, Xiao, Feng, Ke, Yuan, Jin, Liqiang
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
A Frequency-Aware Reinforcement Learning Framework for Suspension Control with Integrated Temporal Features and Expert Guidance2026-01-02094/7/2026
Active suspension systems play a crucial role in improving vehicle ride comfort and handling stability. However, most existing studies focus on the low-frequency range below 20 Hz, leaving the suppression of high-frequency vibrations within 50–500 Hz largely unexplored, even though these vibrations strongly affect in-cabin noise and ride quality. To address this gap, this study introduces a quarter-car suspension model incorporating both bushing dynamics and a rigid-ring tire within a reinforcement learning (RL) framework. A major challenge for RL-based suspension control is its degradation in high-frequency performance. To overcome this issue, we design an innovative training framework that integrates multiple synergistic strategies. First, frequency-domain rewards are incorporated as auxiliary signals to explicitly guide policy optimization in the high-frequency band. Second, long short-term memory (LSTM) networks are embedded in both the Actor and Critic to capture the sequential dependencies of time-domain suspension signals, thereby enhancing temporal feature extraction. Finally, model predictive control (MPC) expert knowledge is injected through reward shaping, which accelerates convergence and stabilizes the learned policy. This combination allows the proposed controller to effectively exploit both data-driven learning and model-based insights for full-band suspension optimization. Simulation results show that the method achieves a 29.67% reduction in body acceleration RMS in the 0–20 Hz range compared with a passive suspension, and further achieves a 62.65% reduction in the 50–500 Hz range relative to a baseline RL controller. By explicitly targeting vibration responses in the in-cabin acoustic control band (20–500 Hz), this study establishes a foundation for integrated suspension-acoustic optimization, offering new insights into ride comfort and NVH enhancement in intelligent vehicles.
zhu, Zhehui, Zhang, Lijun, Meng, Dejian, Hu, Xingyu
Modular Smart Corner Systems for Next-Generation Electric Vehicle Architecture2026-01-06394/7/2026
The transition to software-defined vehicles (SDVs) necessitates a paradigm shift in both control strategies and vehicle architecture. The EU-funded R&D project SmartCorners addresses this challenge by developing integrated, modular, and scalable smart corner systems (SCS) that combine in-wheel motor (IWM)-based propulsion, brake blending, active suspension system, and steer-by-wire functionality in one module. These SCS can be retrofit or smoothly integrated into the highly adaptable skateboard chassis architecture of modern electric vehicles (EVs), enabling scalable deployment across diverse vehicle types. The central approach of this paper is the utilization of artificial intelligence (AI) and machine learning (ML) to implement multi-layer, data-driven control strategies, facilitating real-time actuation, fault mitigation, and user-centric EV architecture. The SmartCorners project strives to demonstrate significant enhancements, including improved real-world driving range due to enhanced energy-efficiency, reduced component and system costs, and a cut-down in development time of EVs, enabled by digital-twin-based design methodologies. Beyond these performance gains, SmartCorners establishes the foundational principles of modularity, adaptability, and software integration that underpin the evolution toward SDVs. The role of thermal and cabin comfort control is completely different for EVs and internal combustion engine vehicles, with the latter using waste heat from the combustion of fossil fuels for cabin heating, ventilation, and cooling (HVAC). In EVs the required energy is directly taken from the traction battery and precise thermal and cabin comfort control affecting essential components of the vehicle but also the user-perceived driving experience. These project achievements highlight a critical bridge between innovation and electrification on component-level, and the holistic software-defined mobility systems of the future.
Ratz, Florian, Armengaud, Eric, Formento, Cecilia, Moscone, Giulia, Sorrentino, Gennaro, Bisciaio, Giorgio, Sorniotti, Aldo, Amati, Nicola, Braun, Daniel, Deibler, Bernd, Boxberger, Valerius, Sottile, Salvatore, Ivanov, Valentin, Fuse, Hiroyuki, Kompara, Tomaž
Design and Performance Analysis of a Modular Transporter Based on Reconfigurable Wheel-Legged Corner Module10-10-04-00313/25/2026
Performing transportation and exploration tasks on rugged terrain requires both high load-bearing capacity and large suspension stroke. However, the corner module configurations applied to challenging terrain have rarely been explored. This article proposes an integrated framework that combines bionic principles with topology graph–based type synthesis. This framework leads to the creation of a reconfigurable wheel-legged mechanism capable of switching between wheeled locomotion and legged gait modes, which is then implemented as a corner module system. First, inspired by the skeletal–muscular system of the equine leg, a structure–function mapping relationship between the biological system and the mechanical system is established. Second, a multi-loop closed-chain mechanism with biomimetic morphology is represented in the form of graph theory. A configuration atlas of the wheel-legged hybrid mechanism is generated based on the contracted graph and open-loop kinematic chains, and configuration optimization is carried out. Third, on the basis of the optimized configuration, a biomimetic vibration isolation system is integrated. Finally, a corner module system that integrates the reconfigurable wheel-legged mechanism with steering, hub motor is designed, as well as the mechanical structure of modular transporters based on the aforementioned corner modular architecture. The vibration reduction performance and various locomotion modes of the modular transporter are verified by multibody dynamic simulation.
Gao, Zhenhai, Zhang, Hanying, Chen, Guoying, Zhang, Sumin, Han, Zongzhi
SBD-YOLO: An Efficient Speed Bump Detector for Active Suspension Preview Control12-09-03-00181/28/2026
Speed bump detection through computer vision and deep learning is essential for advancing active suspension preview control and intelligent driving. Although substantial progress has been made in this field, there remains a need to enhance detection accuracy while reducing computational demands. This article introduces a novel single-stage speed bump detector, the Speed Bump Detector Based on You Only Look Once (SBD-YOLO), which utilizes the YOLOv9 architecture for speed bump identification. To better capture the deep global features of speed bumps, we propose an innovative convolutional module—specifically, a lightweight building block designed for efficient feature extraction—named the Aggregated-MBConv. Furthermore, we design a new YOLO backbone by stacking Mobile Inverted Bottleneck Convolution (MBConv) and Aggregated-MBConv modules, which reduces computational cost while enhancing detection accuracy. Additionally, we introduce a Squeeze-aggregated Excitation (SaE) attention mechanism at the network’s neck, which, through parallel operation, enables collective integration across branches, further improving network performance. A dedicated speed bump dataset was created to validate SBD-YOLO’s effectiveness. Compared to YOLOv9, SBD-YOLO achieves a 9.3% increase in precision, a 2.5% boost in recall, and improvements of 2.2% and 1.4% in mean Average Precision at an Intersection-over-Union (IoU) threshold of 50% (mAP50) and mean Average Precision over IoU thresholds from 50% to 95% (mAP50-95), respectively. Moreover, the number of parameters is reduced by 5 million, and computational complexity is decreased by approximately 82.8%. These results demonstrate the significant potential of SBD-YOLO for active suspension preview control.
Mao, Ruichi, Wu, Jian, Wu, Yukai, Wang, Huiliang, Li, Jun, Wu, Guangqiang
Failure Analysis of Dissimilar Metal Weld Joint of an Air Spring Bracket within an Automotive Active Seat Suspension System2026-26-04871/16/2026
In modern four-wheelers, seat suspension systems play a crucial role in enhancing occupant comfort by mitigating the effects of road unevenness and vibrations. Among these systems, active suspension mechanisms offer advanced performance through complex assemblies involving welded, riveted, and bolted joints. This study investigates the failure of an air spring bracket - a critical component of a pneumatic active suspension system - manufactured by Gas Metal Arc Welding (GMAW) of two dissimilar ferrous materials which are likely to be SAPH440 and S355J2. These different materials were used based on mechanical properties required to perform by their particular part. System level validation tests were conducted to ensure the reliability of the seat suspension system. The one of the validation tests is continuous cyclic fatigue test which is carried out on the complete seat assembly. However, during vibration / cyclic endurance testing, premature failures were observed near the weld joints. Detailed failure analysis using Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and optical microscopy revealed cracks and discontinuities at the weld interfaces. The microstructure in the heat-affected zone (HAZ) exhibited ferrite-Martensite structure with grain coarsening. The fractography reveals the cleavage type and river type fracture morphology which indicates the part failed due to brittle fracture. Inadequate welding of SAPH440 steel can lead to issues such as cracking, distortion, and poor fusion due to its high carbon content and inadequate heat control. The failure analysis study identified that less fusion control of welding parameters and associated thickness and carbon compositions variation which significantly contributed to the component’s fatigue failure. Preventive strategies, including the optimization of sectional thickness and design changes for uniform stress distribution are proposed to improve the reliability of welded assemblies.
Patale Jr, Reshma, Pinjari, Jayant Namdev, Bali, Shirish
Artificial Intelligence in Passenger Cars: Unlocking Intelligent Mobility and Human-Centric Vehicle Innovation2026-26-06721/16/2026
Artificial Intelligence (AI) is radically transforming the automotive industry, particularly in the domain of passenger vehicles where personalization, safety, diagnostics, and efficiency. This paper presents an exploration of AI/ML applications through quadrant of the key pillars: Customer Experience (CX), Vehicle Diagnostics, Lifecycle Management, and Connected Technologies. Through detailed use cases, including AI-powered active suspension systems, intelligent fault code prioritization, and eco-routing strategies, we demonstrate how AI models such as machine learning, deep learning, and computer vision are reshaping both the user experience and engineering workflow of modern electric vehicles (EVs). This paper combines simulations, pseudo-algorithms and data-centric examples of the combined depth of functionality and deployment readiness of these technologies. In addition to technical effectiveness, the paper also discusses the challenges at field level in adopting AI at scale i.e., data scarcity, regulatory, sensory fusion reliability, and user trust. The set of recommendations on safe, modular, and scalable integration roadmap, including the importance of continual learning, hybrid digital twins, and legacy-system interoperability, is provided. By offering a comprehensive yet application-driven perspective, this work serves as both a technical reference and strategic blueprint for stakeholders aiming to embed intelligent systems across the vehicle lifecycle, from predictive diagnostics to real-time adaptive user interfaces.
Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip
Testing and Validation of Future Mobility Vehicles using Realistic Digital Twin of Road Corridors and Tires2026-26-05801/16/2026
The automotive industry is rapidly evolving with technologies such as vehicle electrification, autonomous driving, Advanced Driver Assistance Systems (ADAS), and active suspension systems. Testing and validating these technologies under India’s diverse and complex road conditions is a major challenge. Physical testing alone is often impractical due to variability in road surfaces, traffic patterns, and environmental conditions, as well as safety constraints. Virtual testing using high-fidelity digital twins of road corridors offers an effective solution for replicating real-world conditions in a controlled environment. This paper highlights the representation of Indian road corridors as digital twins in ASAM OpenDRIVE and OpenCRG formats, emphasizing the critical elements required for realistic simulation of vehicle, tire, and ADAS performance. The digital twin incorporates detailed 3D road profiles (X-Y-Z coordinates), capturing the geometry and surface variations of Indian roads. The process of generating the digital twin of road corridor involves mapping road corridors using high-density and high-precision LiDAR scanning, DGPS, and camera sensors. A framework along with mathematical algorithms is developed and tuned specifically for extracting Indian road corridor elements, enabling the creation of accurate and detailed digital representations of roads and associated infrastructure. Proposed digital twin framework provides a robust foundation for evaluating vehicle and tire performance by capturing the unique characteristics of Indian roads and corridors diverse surface types, complex urban layouts along with varying infrastructure elements. It supports accelerated development cycles, improved safety, and optimized comfort, offering automotive OEMs and suppliers a reliable virtual platform for testing and validating next-generation vehicles tailored to Indian driving conditions.
Joshi, Omkar Prakash, Shinde, Vikram, Pawar, Prashant R
A CNN–LSTM–SVM Framework for Mapping Driving Styles to Adaptive Suspension Modes10-10-02-00111/9/2026
Personalized suspension control is pivotal for enhancing vehicle dynamics and ride comfort in intelligent driving systems. This study proposes a driver style recognition model integrating convolutional neural network (CNN) and long–short-term memory (LSTM) networks to match suspension modes with driving styles, validated via a MATLAB–Python co-simulation platform. Time-series multi-source sensor data (throttle position, steering angle, braking intensity) are processed by CNN to extract spatiotemporal features and by LSTM to capture long-term temporal dependencies, enabling accurate classification of aggressive, smooth, and conservative driving styles. A support vector machine (SVM) maps these styles to optimal suspension modes—sport, comfort, or economy—forming an end-to-end framework. Simulation results demonstrate that the CNN–LSTM model achieves an 88% classification accuracy, a 17.33% improvement over the genetic algorithm-optimized backpropagation (GA-BP) model. The SVM-based matching yields matching degrees of 0.95, 0.90, and 0.88 for the three styles, respectively, confirming high accuracy and robustness. Compared to baseline models, the proposed approach excels in prediction accuracy, convergence speed, computational efficiency, generalization, and stability. These findings offer a robust solution for personalized suspension control, enhancing vehicle dynamics and driver comfort.
Wang, Zhuang, Liu, Jiang, Sun, Haoyu, Yuan, Yinghao, Liu, Jianze, Chen, Xiaofei, Wang, Honglin
A Coordinated Approach for Enhancing Handling Stability and Ride Comfort of Wheel-Legged Vehicles2025-01-732612/31/2025
This paper presents StaRide, a novel coordinated control framework for wheel-legged vehicles that simultaneously addresses handling stability and ride comfort challenges. The proposed approach integrates three key components: (1) a nonlinear model predictive control (NMPC) scheme enhanced with roll-steering dynamics for trajectory optimization, (2) an linear quadratic regulator (LQR)-based active suspension system utilizing leg mechanisms as virtual dampers, and (3) an adaptive impedance controller with behavior-dependent stiffness adjustment. The framework demonstrates significant improvements over conventional methods through extensive experimental validation, achieving 42% higher stable steering speeds (4.8 m/s vs 3.38 m/s), 46% pitch angle reduction on obstacles, and 39% lower vibration RMS on rough terrain. Real-time performance is maintained with 100Hz NMPC and 500Hz LQR execution rates. Results show particular effectiveness in preventing rollover during aggressive maneuvers while ensuring comfort during normal operation, establishing a new paradigm for wheel-legged vehicle control that successfully bridges the stability-comfort trade-off. The system's generalizability suggests potential applications in other hybrid locomotion platforms.
Xu, Mingfan, Xu, Chuyan, Yang, Ziyi, Yuan, Haoyang, Zhu, Zhewei, Qin, Yechen
Deep Reinforcement Learning–Based Control Strategy for Electro-Hydrostatic Active Suspension15-18-03-00167/9/2025
A DRL (deep reinforcement learning) algorithm, DDPG (deep deterministic policy gradient), is proposed to address the problems of slow response speed and nonlinear feature of electro-hydrostatic actuator (EHA), a new type of actuation method for active suspension. The model-free RL (reinforcement learning) and the flexibility of optimizing general reward functions are combined with the ability of neural networks to deal with complex temporal problems through the introduction of a new framework called “actor-critic”. A EHA active suspension model is developed and incorporated into a 7-degrees-of-freedom dynamics model of the vehicle, with a reward function consisting of the vehicle dynamics parameters and the EHA pump–valve control signals. The simulation results show that the strategy proposed in this article can be highly adapted to the nonlinear hydraulic system. Compared with iLQR (iterative linear quadratic regulator), DDPG controller exhibits better control performance, achieves the EHA control objective at faster speed, and notably improves the ride comfort and handling stability of the car. Moreover, DDPG’s optimized valve–pump joint control strategy can reduce the energy consumption of the EHA system and improve the life of the hydraulic components while ensuring the control accuracy, solving the problem of low reliability of the active suspension system.
Wang, Jiawei, Guo, Huiru, Deng, Xiaohe
Experimental Investigation on Genetic Algorithm Optimized Proportional Integral Derivative Based Active Suspension System2025-01-00145/5/2025
In this work, Genetic Algorithm (GA) optimized Proportional Integral Derivative (PID) controller is employed in the active suspension. The PID gain values are optimally tuned based on the objective function by the Integral Time Absolute Error (ITAE) criteria of various suspension measures like vehicle body displacement, suspension and tire deflections. The proposed GAPID controller is experimentally validated through the 3-DOF quarter-car (QC) test rig model. The fabricated model with passive suspension system (PASS) and active suspension system (ACSS) with an electrical actuator is presented. The schematic representation of the fabricated test set-up with and without ACSS is also illustrated. Further, simulation and experimental response of the fabricated model with and without ACSS are compared. It is identified that the proposed GAPID controller attenuates the sprung mass acceleration by about 41.64 % and 29.13 % compared with PASS for the theoretical as well as experimental cases respectively.
A, Arivazhagan, Kandavel, Arunachalam
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
Coordinated Control Strategy for Longitudinal, Lateral, and Vertical Motions of Distributed Electric Vehicles Based on Model Predictive Control2025-01-83004/1/2025
Distributed electric vehicles, equipped with independent motors at each wheel, offer significant advantages in flexibility, torque distribution, and precise dynamic control. These features contribute to notable improvements in vehicle maneuverability and stability. To further elevate the overall performance of vehicles, particularly in terms of handling, stability, and comfort, this paper introduces an coordinated control strategies for longitudinal, lateral, and vertical motion of distributed electric vehicles. Firstly, a full-vehicle dynamics model is developed, encompassing interactions between longitudinal, lateral, and vertical forces, providing a robust framework for analyzing and understanding the intricate dynamic behaviors of the vehicle under various operating conditions. Secondly, a vehicle motion controller based on Model Predictive Control is designed. This controller employs a sophisticated multi-objective optimization algorithm to manage and coordinate several critical subsystems, including Active Front-Wheel Steering, Direct Yaw Moment Control, Active Suspension System, and Anti-Slip control, significantly enhancing the vehicle's overall handling performance and coordination among implementation systems Finally, to prevent tire slippage and lock-up, an optimized torque distribution method based on slip ratio feedback is proposed. This method constraint torque distribution by calculating the maximum transmissible longitudinal force through the anti-slip control module, achieving integrated anti-slip and torque allocation. The proposed control strategy is validated through a comprehensive co-simulation platform integrating CarSim and Simulink. Simulation results demonstrate that the proposed scheme effectively improves vehicle ride comfort and enhances maneuverability and stability under various driving conditions. This research highlights the extensive application potential and practical engineering value of the proposed cooperative control strategy in advancing the performance of distributed electric vehicles.
Jia, Jinchao, Yue, Yang, Sun, Aobo, Liu, Xiao-ang
Improved Model and Physical Prototype of an Online Corrective Look-Ahead Road Profiling System (CLARPS) for Active Suspension Applications2025-01-87904/1/2025
Online road profiling capability is required for automotive active suspension systems to be realized in a consumer and commercial landscape. One challenge that impedes the realization of these systems is the need for the online road profiler to maintain an optimal spatial resolution of the oncoming road profile. Shifting of the road profiling sensor measurement frame of reference due to body motion experienced by the vehicle can negatively impact profiling accuracy. Prior work proposed a corrective look-ahead road profiling system (CLARPS) and demonstrated the CLARPS architecture and initial MATLAB/Simulink simulation environment. First, this work further develops the robust simulation environment. The simulation allows the look-ahead viewing angles to be optimized for the best road profile spatial resolution and facilitates a study on the impact of road profiler sensor location on the accuracy of the generated road profile. Second, this work introduces a lab-scale physical CLARPS prototype. The CLARPS prototype is validated through the use of an established test stand and test cases, with empirically gathered road profile results.
Morison, Dane, Mynderse, James
The Model Predictive Control of Dual-Chamber Active Air Suspension Based on Road Preview2025-01-87894/1/2025
Adverse weather conditions such as rain and snow, as well as heavy load transportation, can cause varying degrees of damage to road surfaces, and untimely road maintenance often results in potholes. Perception sensors equipped on intelligent vehicles can identify road surface conditions in advance, allowing each wheel’s suspension to actively adjust based on the road information. This paper presents an active suspension control strategy based on road preview information, utilizing a newly designed dual-chamber active air suspension system. It addresses the issue of point cloud stratification caused by vehicle body vibrations in onboard LiDAR data. The point cloud is processed through segmentation, filtering, and registration to extract real-time road roughness information, which serves as preview information for the suspension control system. The MPC algorithm is applied to actively adjust the nonlinear stiffness and damping of the suspension’s dual-chamber air springs, enhancing suspension response speed and accuracy. The effectiveness of the active air suspension MPC method under real-time road sensing is validated through co-simulation using Matlab/Simulink and CarSim. Vehicle ride comfort is used as the evaluation criterion, demonstrating that the integrated sensing and control approach can effectively reduce vehicle.
Dong, Fuxin, Shen, Yanhua, Wang, Kaidi, Liu, Zuyang, Qian, Shuo
Modeling and Analysis of Comfort Braking Control Based on Brake-by-Wire and Active Suspension Systems10-09-02-00112/7/2025
As wire control systems advance, they have given rise to a diverse suite of advanced driver assistance services and sophisticated fusion control capabilities. This article presents an innovative strategy for achieving comfortable braking in electric vehicles, propelled by the unwavering goal of enhancing driving experience. By integrating active suspension systems with brake-by-wire technology, the approach ensures that drivers retain their confidence throughout the braking process. The brake-by-wire system adeptly discerns the driver’s braking intent through the pedal’s displacement sensor. Utilizing this technology, we have developed a pioneering function aimed at delivering comfort braking control (CBC). This function not only refines the braking experience but also solidifies the driver’s trust in the braking system. Designed to counteract the head nodding effect during vehicle deceleration, the CBC system minimizes or even eradicates the jarring sensation of pitching for both the driver and passengers. The algorithm detailed in this article has undergone rigorous validation through extensive real-world vehicle testing. The results indicate that the proposed method markedly improves key performance metrics: it enhances the pitch angle by 37.74%, reduces the pitch angle speed by 77.12%, shortens the convergence time by 57.14%, and diminishes the pitch angle peak amplitude by 45.65%, all within a 0.3g braking deceleration scenario. This groundbreaking function has now been successfully implemented in mass production vehicles.
Tian, Boshi, Li, Liang, Liao, Yinsheng, Lv, Haijun, Qu, Wenying, Hu, Zhiming, Sun, Yue
Height Control Method for Air Suspension Systems Based on Model-Free Adaptive Control and Improved Genetic Algorithm15-18-02-00091/17/2025
This article presents a height control method for air suspension systems, which are influenced by strong nonlinearity and multiple coupling factors, based on model-free adaptive control (MFAC) using full-form dynamic linearization (FFDL). To address the impact of different damping coefficients of the shock absorber on the height control effect, an improved genetic algorithm is employed to globally optimize the relevant parameters involved in the design of the control law, thereby enhancing the height control performance. The precision of modeling the air suspension system has a direct impact on the simulation of both static and dynamic vehicle models, as well as the accuracy of height control. In this article, an equivalent thermodynamic model of the air suspension system is established based on the principle of energy conservation for height control research. Considering the nonlinearity of the air suspension system and the need to make additional assumptions before modeling, a MFAC method using FFDL is adopted for controller design. Traditional height control methods do not consider the impact of changes in the shock absorber damping coefficient on the height control effect. For different damping coefficients, the body height tracking error is large when using the same height control law initialization parameters. Therefore, an improved genetic algorithm is employed to globally optimize the MFAC parameters under different damping states. The effectiveness of the thermodynamic model of the air suspension system and the MFAC method for height control, with parameters tuned using the improved genetic algorithm, was validated through MATLAB/Simulink simulations.
Yao, Jiyang, Wu, Guangqiang, Wu, Jian, Yang, Yuchen, Yan, Xudong
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
Active Hydro-Pneumatic Suspension Active Disturbance Rejection Sliding Mode Control for Improved Vehicle Stability2024-28-021512/5/2024
Hydro-pneumatic suspension is widely used because of its desirable nonlinear stiffness and damping characteristics. However, the presence of parameter uncertainties and high nonlinearities in the system, lead to unsatisfactory control performance of the traditional controller in practical applications. In response to this challenge, this paper proposes a novel stability control method for active hydro-pneumatic suspension (AHPS). Firstly, a nonlinear mathematical model of the hydro-pneumatic suspension, considering the seal friction, is established based on the hydraulic principle and the knowledge of Fluid dynamics. On the basis of the established hydro-pneumatic suspension nonlinear model, a vehicle dynamics model is established. Secondly, an active disturbance rejection sliding mode controller (ADRSMC) is designed for the vertical, roll, and pitch motions of the sprung mass. The lumped disturbance caused by the model nonlinearities and uncertainties is estimated by the extended state observer (ESO), which is then integrated into the sliding mode control law. This allows the control law to actively adapt to the working state of the suspension system, which can effectively address the impact of uncertainties and nonlinearities on the system. Finally, the simulations are carried out on bump and random roads, two typical working conditions. The results show that the proposed ADRSMC can reduce the amplitude of vehicle acceleration by more than 50% compared to traditional passive hydro-pneumatic suspension, and the optimization effect is better than active disturbance rejection control ADRC). It significantly improves the stability of the vehicle. This study provides a valuable reference for the design of active hydro-pneumatic suspension control strategies.
Niu, Changsheng, Liu, Xiaoang, Jia, Xing, Gong, Bo, Xu, Bo
Passenger Car Air Spring Suspension: Open-System Modeling and Experimental Verification2024-01-510010/24/2024
Air suspension systems are increasingly in demand in high-end cars due to their ability to vary ride height based on vehicle loads, road conditions, and speeds. This trend has driven manufacturers to enhance the performance of these systems. Predicting and optimizing the performance of the air spring system for various vehicle loads and conditions has become essential. The performance of an air suspension system is typically measured by its ability to suspend the vehicle within a specified target time. Therefore, it is necessary to model the air spring system—including the air spring, compressor, pneumatic lines, and valves—and integrate it with the vehicle. This modeling helps in predicting performance and optimizing the system. Additionally, a validated system model enables other important calculations, such as sizing the valves, pneumatic hoses, and compressors. In this study, a complete air spring system model has been developed alongside a 15-degrees-of-freedom car chassis to achieve the highest possible accuracy regarding leveling times while maintaining reasonable simulation times. The air spring components were validated with actual measurements, and the system was subsequently validated using an experimental setup. The system’s performance was simulated and then compared with actual vehicle measurements, resulting in simulation outcomes that were comparable to the measurements.
Ahmed, Saad Anwar, Hupfeld, Jan, Rajput, Brijesh
A Simulation Model for an Online Corrective Look-Ahead Road Profiling System (CLARPS) for Active Suspension Applications2024-01-27584/9/2024
Online road profiling capability is required for automotive active suspension systems to be realized in a commercial landscape. The challenges that impede the realization of these systems include a profiler’s ability to maintain an optimal resolution of the oncoming road profile (spatial frequency). Shifting of the profile measurement frame of reference due to body motion disturbances experienced by the vehicle also negatively impacts profiling capability. This work details the early development of a corrective look-ahead road profiling system (CLARPS) and its control logic. The CLARPS components are introduced and additional focus will be given to the development of the angle generating function (AGF) and how it drives the ability of the system to optimize look-ahead viewing angles for the best spatial frequency resolution of a road profile. The CLARPS simulation environment is demonstrated with numerical comparison of simulated road profiles at varying vehicle speeds.
Morison, Dane, Mynderse, James
An Active Suspension Control Strategy for Planet Rover on Rough Terrain2024-01-23004/9/2024
The soft and rough terrain on the planet's surface significantly affects the ride and safety of rovers during high-speed driving, which imposes high requirements for the control of the suspension system of planet rovers. To ensure good ride comfort of the planet rover during operation in the low-gravity environment of the planet's surface, this study develops an active suspension control strategy for torsion spring and torsional damper suspension systems for planet rovers. Firstly, an equivalent dynamic model of the suspension system is derived. Based on fractal principles, a road model of planetary surface is established. Then, a fuzzy-PID based control strategy aimed at improving ride comfort for the planet rover suspension is established and validated on both flat and rough terrains. This study provides an advanced suspension system control strategy for planet rovers' ride comfort and safety during high-speed driving, ensuring the smooth operation of vehicles on the rough extraterrestrial terrain.
Liu, Jun, Zhang, Kaidi, Shi, Junwei, Wu, Jinglai, Zhang, Yunqing
Research on the Control Strategy of Electric Vehicle Active Suspension Based on Fuzzy Theory2024-01-22904/9/2024
The performance of suspension system has a direct impact on the riding comfort and smoothness. For the traditional suspension can not effectively alleviate the impact of road surface and the poor anti-vibration performance, The dynamics model of vehicle suspension system is established, and the control model of vehicle four-degree-of-freedom active suspension is designed with fuzzy control strategy. On this basis, a comprehensive simulation model of the control model of vehicle active suspension coupled with road excitation is established. and the ride comfort of vehicles under different types of suspension are tested through Simulink. The simulation results show that compared with the passive suspension, the reduction of vehicle acceleration and dynamic deformation of the active suspension controlled by fuzzy PID can reach 33.76% and 22.45%. and the reduction of pitch Angle speed and dynamic load of the active suspension controlled by fuzzy PID can reach 16.18% and 10.72%. Under fuzzy PID control, the amplitude of each evaluation index of active suspension in the suspension system is substantially reduced than that of the passive suspension, and the root-mean-square value decreases by about 10% on average. It can be seen that the active suspension with fuzzy PID control can improve the performance of the suspension system on the basis of ensuring the stability and rapid response of the system, and can well reduce the random vibration caused by the impact of the vehicle on the random road surface during the driving process, improve the ride comfort, smoothness and ride safety of the vehicle, and achieve a good control effect on the vehicle suspension.
Jing, Li Jing
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.
Analysis and Design of Suspension State Observer for Wheel Load Estimation2024-01-22854/9/2024
Tire forces and moments play an important role in vehicle dynamics and safety. X-by-wire chassis components including active suspension, electronic powered steering, by-wire braking, etc can take the tire forces as inputs to improve vehicle’s dynamic performance. In order to measure the accurate dynamic wheel load, most of the researches focused on the kinematic parameters such as body longitudinal and lateral acceleration, load transfer and etc. In this paper, the authors focus on the suspension system, avoiding the dependence on accurate mass and aerodynamics model of the whole vehicle. The geometry of the suspension is equated by the spatial parallel mechanism model (RSSR model), which improves the calculation speed while ensuring the accuracy. A suspension force observer is created, which contains parameters including spring damper compression length, push rod force, knuckle accelerations, etc., combing the kinematic and dynamic characteristic of the vehicle. Subsequently, the wheel load can be obtained by solving the above nonlinear system using Extended Kalman Filtering (EKF). Validation experiments are conducted on a quarter-suspension model as well as a Formula Student race car under standard working conditions. The car is equipped with sensors for the signals required by the algorithm as well as signal processing units. While calculations are performed, the conventional acceleration-based estimation method is used for comparison. The experimental results show that the measurement error of the method in this paper is significantly smaller than that of the traditional method, and it has higher sensitivity to dangerous conditions such as bumps and rollovers, which is of greater significance for the usage of wheel load for vehicle control and active safety.
Zeng, Tianyi, Liu, Zeyu, He, Chenyu, Zeng, Zimo, Chen, Haotian, Zhang, Feiyang, Fu, Kai, Chen, Xinbo
Exploring Capabilities of Hydraulic Actuators to Achieve Vehicle Ride Targets in Frequency Range beyond Their Operational Bandwidth2024-26-00601/16/2024
Active suspension systems employ sophisticated control algorithms to deliver superior comfort in vehicles. However, the capabilities of these algorithms are limited by the physical constraints of actuators. Many vehicles use hydraulic actuators in their active suspension system, which use fluid movement to control suspension motion. These systems inherently have slower response times due to the nature of fluid flow and the time required to build up or release pressure within the hydraulic system. Typically, hydraulic systems operate in a low bandwidth of 0-5 Hz. This limits their capability to only meeting vehicle’s primary ride targets which typically lie below 5 Hz. Although they can be tuned to operate at a slightly higher frequency range (up to 10 Hz), they perform poorly in attenuating the secondary ride vibration, i.e., 5 – 25 Hz. This paper focuses on investigating the possible hardware and subsequently control capabilities that can allow us to affect the vehicle ride well beyond the actuator bandwidth. The aim is to conduct a detailed simulation-based analysis to investigate the possibility of expanding the effective operational frequency range of hydraulic actuators. In this work, we studied force applications in the frequency range of 0 - 5 Hz with different amplitudes at four corner modules and evaluated the ride performance using Fast Fourier Transformation (FFT). This paper concludes with a discussion about the extent of Hydraulic Actuator limitations and the required technological advancements for improving the secondary ride response.
Agrawal, Ayush, Negi, Ayush, Joshi, Divyanshu
Hierarchical Control Strategy for Active Suspension Equipped with an Electromagnetic Actuator2023-01-707712/31/2023
Electromagnetic suspension systems have increasingly gained widespread attention due to their superiority in improving ride comfort while providing fast response, excellent controllability and high mechanical efficiency, but their applications are limited due to the accuracy of the underlying control actuation tracking. For addressing this problem, this study presents a novel hierarchical control strategy for an electromagnetic active suspension (EMAS) system equipped with an electromagnetic actuator (EMA) structure. The structure of the EMA device and the working principle of the motion conversion model are introduced in detail first, and the motion conversion equation is derived based on the force-torque relationship. Based on this, a linear quadratic regulator (LQR) control method is proposed to be applied to a half-vehicle suspension system to improve the vibration isolation performance of the vehicle and ensure the ride comfort. Then, the underlying layer control of the permanent magnet synchronous motor (PMSM) based on field-oriented control (FOC) is adopted to tracking the active control forces generated by the upper LQR controller. Immediately afterwards, the EMA converts the torque generated by the motor into vertical forces acting on the suspension through rational synergies between the upper LQR controller and the underlying motor controller, which ultimately achieves active control of the vehicle suspension system. The simulations are carried out from the perspective of the half-vehicle integrated with the EMA, which demonstrate that the proposed EMAS system has greatly reduced vehicle vertical and pitch accelerations compared to the conventional passive suspension, significantly improving the ride comfort and vibration isolation effect on external excitation.
Lai, Jiewen, Zhang, Bangji, Qin, An, Zeng, Sheng, Wang, Shichen
Multi-Objective Switching Control of Active Suspension Based on Forward-Looking Preview2023-01-706012/20/2023
The active suspension system has strong application potential in electric vehicles (EV) due to its superior controllability. However, the feedback delay of vehicle status information will degrade the control performance of active suspension. This paper investigates the multi-objective control of preview active suspension based on forward-looking information perception. An integrated model including the forward-looking system, vehicle dynamics system and control switching system is established. First, a multi-degree-of-freedom vehicle dynamics model including the input-output system is created, then, an LQR active suspension controller is designed, secondly, a pareto solution set with multiple different target solutions is obtained by calculation, finally, a forward-looking preview mode-switching controller that can select different control strategies according to the road conditions ahead is designed. The results show that the controller can intelligently switch the control strategy of the controller according to the different working condition information detected by the forward-looking system, the controller can provide anti-roll control in cornering conditions, anti-pitch control in acceleration and braking conditions, and comfort control in straight-line driving.
Wan, Ma, Wan, Kechang, Hu, Yiming
Concept, Implementation, and Performance Comparison of a Particle Filter for Accurate Vehicle Localization Using Road Profile Data10-07-03-00258/25/2023
A precise knowledge of the road profile ahead of the vehicle is required to successfully engage a proactive suspension control system. If this profile information is generated by preceding vehicles and stored on a server, the challenge that arises is to accurately determine one’s own position on the server profile. This article presents a localization method based on a particle filter that uses the profile observed by the vehicle to generate an estimated longitudinal position relative to the reference profile on the server. We tested the proposed algorithm on a quarter vehicle test rig using real sensor data and different road profiles originating from various types of roads. In these tests, a mean absolute position error of around 1 cm could be achieved. In addition, the algorithm proved to be robust against local disturbances, added noise, and inaccurate vehicle speed measurements. We also compared the particle filter with a correlation-based method and found it to be advantageous. Even though the intended application lies in the context of proactive suspension control, other use cases with precise localization requirements such as self-driving cars might also benefit from our method.
Anhalt, Felix, Hafner, Simon
The Integrated Trajectory Tracking, Yaw Stability and Roll Stability Model Predictive Control for Autonomous Vehicle in Limited Handling Condition2023-01-06674/11/2023
In the current literature, the research studies on the trajectory tracking control and stability control strategy for autonomous vehicles in limited condition mostly focus on the yaw plane control, but few of the studies have considered the combined control performance of trajectory tracking, yaw and roll stability, and the roll stability is critical under the extreme cornering condition for autonomous vehicles. Aiming at the above shortages, this study designs the model predictive control (MPC) strategy for the autonomous vehicles under the limited handling condition, which integrates the front and rear wheel active steering control, four-wheel independent drive and braking control and active suspension control to comprehensively improve the trajectory tracking accuracy, yaw plane stability and roll plane stability of the vehicle under the extreme condition. In the internal prediction model of the MPC, the yaw plane dynamics, roll plane dynamics and suspension system models are considered to better coordinate the yaw plane and roll plane dynamics control. Also the different control delays of steering, driving, braking and suspension control actuators are considered in the model. In addition, in order to improve the vehicle yaw stability, the soft constraints of wheel longitudinal slip and lateral side-slip angle are designed in the optimization objective function of the MPC. Furthermore, based on the analysis on the coupling effect of the steering, traction or brake and active suspension control on the trajectory tracking and vehicle dynamics stability, the scaling factors of MPC optimization cost function are normalize and carefully tuned to achieve the best performance. Finally, the effectiveness and computational efficiency of the designed integrated MPC strategy is verified by simulation based on high fidelity vehicle dynamics model.
Li, Boyuan, Li, Wenfei, Hua, Wei, Velenis, Efstathios
Actively Articulated Wheeled Architectures for Autonomous Ground Vehicles - Opportunities and Challenges2023-01-01094/11/2023
Traditional ground vehicle architectures comprise of a chassis connected via passive, semi-active, or active suspension systems to multiple ground wheels. Current design-optimizations of vehicle architectures for on-road applications have diminished their mobility and maneuverability in off-road settings. Autonomous Ground Vehicles (AGV) traversing off-road environments face numerous challenges concerning terrain roughness, soil hardness, uneven obstacle-filled terrain, and varying traction conditions. Numerous Active Articulated-Wheeled (AAW) vehicle architectures have emerged to permit AGVs to adapt to variable terrain conditions in various off-road application arenas (off-road, construction, mining, and space robotics). However, a comprehensive framework of AAW platforms for exploring various facets of system architecture/design, analysis (kinematics/dynamics), and control (motions/forces) remains challenging. While current literature on the AAW system incorporates modeling and control from the legged and wheeled-legged robots community, it lacks a systematic process of architecture selection and motion control that should be developed around critical quantifiable performance parameters. This paper will: (i) analyze a broad body of literature; and (ii) identify modeling and control techniques that can enable the efficient development of AAW platforms. We then analyze key performance measures with respect to traversability, maneuverability, and terrainability, along with an experimental simulation of an AAW vehicle traversing over uneven terrain and how active articulation could achieve some of the critical performance measures. Against the performance parameters, gaps within the existing literature and opportunities for further research are identified to potentially enhance AAW platforms’ performance.
Mehta, Dhruv, Kosaraju, Krishna Chaitanya, Krovi, Venkat N
Design and Validation of a High-Level Controller for Automotive Active Systems10-07-01-000611/7/2022
Active systems, from active safety to energy management, play a crucial role in the development of new road vehicles. However, the increasing number of controllers creates an important issue regarding complexity and system integration. This article proposes a high-level controller managing the individual active systems—namely, Torque Vectoring (TV), Active Aerodynamics, Active Suspension, and Active Safety (Anti-lock Braking System [ABS], Traction Control, and Electronic Stability Program [ESP])—through a dynamic state variation. The high-level controller is implemented and validated in a simulation environment, with a series of tests, and evaluate the performance of the original design and the proposed high-level control. Then, a comparison of the Virtual Driver (VD) response and the Driver-in-the-Loop (DiL) behavior is performed to assess the limits between virtual simulation and real-driver response in a lap time condition. The main advantages of the proposed design methodology are its simplicity and overall cooperation of different active systems, where the proposed model was able to improve the vehicle behavior both in terms of safety and performance, giving more confidence to the driver when cornering and under braking. Some differences were discovered between the behavior of the VD and the DiL, especially regarding the sensitivity to external disturbances.
de Carvalho Pinheiro, Henrique, Carello, Massimiliana
Investigation of Vehicle Stability by Integration of Active Suspension, Torque Vectoring, and Direct Yaw Control10-06-04-002910/5/2022
In this article, the integrated vehicle stability control strategy by a combination of active suspension (AS), torque vectoring control (TVC), and direct yaw control (DYC) is proposed to investigate the improvement of vehicle stability. By considering the differences of control targets for variable vehicle subsystems, the proposed strategy includes the three levels of hierarchical structure to coordinate these vehicle subsystems for optimal functions in relation to the vehicle subsystems. At the upper level, the vehicle estimates the posture and dynamic state. At the middle level of the structure, the method of coordination is introduced. Furthermore, the designed AS is based on H∞ logic theory. The TVC design is based on the principle of indirect yaw moment theory, and the DYC design is based on linear quadratic regulator (LQR) control algorithm are demonstrated at the lower level. In order to verify the control effect, the MATLAB/Simulink platform is used for the establishment of the model and simulation. Comparison between the simulation results and experimental results illustrate that the proposed integrated AS/TVC/DYC control system is preferred over the uncontrolled system.
Hu, Zhiming, Liao, Yinsheng, Liu, Jianjian, Xu, Haolun
Road Preview Control for Active Suspension System10-06-04-00258/23/2022
The industrialization of the measurement systems of road profiles enabled the deployment of the road preview control strategies for the vehicle-controlled suspensions. This article proposes a new active suspension control strategy in which a model reference controller (MRC) is improved through the road preview capability. The road preview control uses the feed-forward road input signals and the feedback vehicle state signals as controller inputs. A thirteen degree-of-freedom (DOF) full vehicle vertical dynamics model including stabilizer bars is used. Eight proportional integral derivative (PID) controllers for sprung and unsprung masses have been used in the control strategy. The controller parameters including the preview distance have been obtained by using a gradient-based optimization routine with an objective function that includes both ride comfort and road holding. The ride performance of the road preview control strategy is evaluated by using a measured stochastic road profile. The results illustrated the potential of the road preview control strategy to improve the ride performance compared with the MRC without road preview control.
Kaldas, Mina M., Soliman, Aref M.A., Abdallah, Sayed A., Mohammad, Samah S., Amien, Fomel F.
Experimental Assessment of a Controlled Slippage Magnetorheological Automotive Active Suspension for Ride Comfort10-06-04-00248/23/2022
Active suspensions can alter the dynamic behavior of a vehicle in real time to respond optimally to any given operating scenario. Today’s active suspension technologies such as hydraulics, rotary electromagnetics, and linear electromagnetics do offer performance gains but these gains are outweighed by important disadvantages including high power consumption, low quality of force, and high costs and weights. Controlled slippage magnetorheological (MR) actuators are an emerging alternative actuation technology that is light, compact, power dense, and produces a high-quality force, making it ideal for active suspension applications. This article conducts an in-depth experimental assessment of the potential of MR actuators to increase vehicle ride comfort quality when used as active suspensions. Four high power MR actuators are installed on a BMW 330Ci and tests are performed on a closed road. Results show that with an impedance controller, comfort is increased by 67% at 65 km/h and by 61% at 80 km/h. These results compare favorably with the best-in-class electromagnetic active suspension technologies reported to date and suggest that MR actuators are promising for automotive active suspensions.
Turcotte, Jérôme, East, William, Plante, Jean-Sébastien
Optimum Response of a Nonlinear Passive Vehicle Suspension System under Random Road Excitations02-16-01-00047/7/2022
The objective of the present article is to design a nonlinear passive suspension system for an automobile subjected to random road excitation which generates a performance as close to a fully active suspension system as possible. Linear Quadratic Regulator (LQR) control is used to synthesize an active suspension system. The control forces corresponding to the nonlinear passive suspension and the active suspension are equated, and the parameters are optimized as the performance error between the two systems is reduced. The nonlinear equations of motion are reduced to equivalent linear equations, where the system states are a function of the vehicle response statistics, by using the equivalent linearization method. The performance of the optimized nonlinear model and the linear model are compared with the performance of the LQR control active suspension system. The nonlinear model performs better than the linear system with chosen parameters. The optimized system achieves almost an equal response to the active suspension system for ride comfort and road holding over the specified velocity range. The optimum response of a passive suspension system with nonlinear suspension elements is achieved using a novel optimization method. This method provides design flexibility, and it has great engineering importance for application in the design of various vibration control devices.
Satyanarayana, V. S. V., Sharma, Rakesh Chandmal, Sateesh, B., Gopala Rao, L. V. V., Mohan Rao, N., Palli, Srihari
Generalized Vehicle DynamicsR-4984/26/2022
Author Daniel E. Williams, an industry professional with more than 30 years of experience in chassis control systems from concept to launch, brings this experience and his unique approach to readers of Generalized Vehicle Dynamics. This book makes use of nomenclature and conventions not used in other texts. This combination allows the derivation of complex vehicles that roll with multiple axles, any of which can be steered, to be directly predicted by manipulation of a generalized model. Similarly the ride characteristics of such a generalized vehicle are derived. This means the vehicle dynamic behavior of these vehicles can be directly written from the results derived in this work, and there is no need to start from Newton's Second Law to create such insight. Using new and non-standard conventions allows wider applicability to complex vehicles, including autonomous vehicles. Generalized Vehicle Dynamics is divided into two main sections-ride and handling-with roll considered in both. Each section concludes with a case study that applies the concepts presented in the preceding chapters to actual vehicles. Chapters include Simple Suspension as a Linear Dynamic System, The Quarter-Car Model, The Pitch Plane Model, The Roll Plane Mode, Active Suspension to Optimize Ride, Handling Basics, Reference Frames, New Conventions, Two-Axle Yaw Plane Model, Rear Axle Steering and Lanekeeping, Two-Axle Vehicles that Roll, Three-Axle Vehicle Dynamics, Generalized Multi-Axle Vehicle Dynamics and Automated Vehicle Architecture from Vehicle Dynamics. "A fresh and more inclusive book that lays out much new material in vehicle dynamics." - L. Daniel Metz, Ph.D.
Williams, Daniel
Simulation-Based Development for Active Suspension Control for Automated Driving Vehicles—Evaluation of Transferability to Real-World Testing12-05-03-00214/25/2022
Due to the transition of the driver to a passenger as well as the option of non-driving tasks, automated driving will necessitate adjustments of driving dynamics. In order to face higher comfort requirements and mitigate motion sickness not only horizontal dynamics but also vertical dynamics should be concerned. Therefore, we developed a novel control algorithm for active suspension systems, which takes the requirements of autonomous vehicles into account. Due to safety, cost reasons, and the unavailability of automated test vehicles, the controller was built up, tested, and tuned in simulation before final in-car testing. In this article we introduce a combined simulation and testing process for suspension control systems with focus on comfort measures. We successfully apply the method to the mentioned active suspension control algorithm with good accordance between simulation and measurement for low-frequency excitation.
Jurisch, Matthias, Herold, Sven, Atzrodt, Heiko, Bauer, Jannik Lukas
Electric Vehicle Corner Architecture: Driving Comfort Evaluation Using Objective Metrics2022-01-09213/29/2022
The presented paper is dedicated to the driving comfort evaluation in the case of the electric vehicle architecture with four independent wheel corners equipped with in-wheel motors (IWMs). The analysis of recent design trends for electrified road vehicles indicates that a higher degree of integration between powertrain and chassis and the shift towards a corner-based architecture promises improved energy efficiency and safety performances. However, an in-wheel-mounted electric motor noticeable increases unsprung vehicle mass, leading to some undesirable impact on chassis loads and driving comfort. As a countermeasure, a possible solution lies in integrated active corner systems, which are not limited by traditional active suspension, steer-by-wire and brake-by-wire actuators. However, it can also include actuators influencing the wheel positioning through the active camber and toe angle control. Such a corner configuration is discussed in the paper as applied to a sport utility vehicle (SUV). A new chassis design was developed and tested for this reference vehicle using multi-body dynamics simulation. The integrated operation of the active suspension and the wheel positioning control has been analyzed in this study with different driving scenarios and objective metrics for driving comfort evaluation. Additionally, handling and stability tests have also been performed to confirm that new systems do not deteriorate driving safety. The obtained results contribute to a comprehensive assessment of IWM-based architecture, formulated from a driving comfort perspective that is helpful for further designs of electric vehicle corners.
Zuraulis, Vidas, Kojis, Paulius, Marotta, Raffaele, Šukevičius, Šarūnas, Šabanovič, Eldar, Ivanov, Valentin, Skrickij, Viktor
Sensitivity Analysis of Ride Characteristics of Four-Wheel Vehicle under Random Road Surface Undulations2022-01-50113/2/2022
The vehicle performance is examined based on its specific performance indices. These specific performance indices include stability, ride comfort, steering ability, etc. The vehicle ride comfort is an important factor of vehicle quality and receiving large attention. The majority of previous investigations are focused on vertical vibration analysis of the sprung mass of the vehicle subjected to vertical excitations from the road surface. This study evaluates the ride characteristics of a coupled vertical-lateral 13 degrees of freedom (DoF) full-car model of a light passenger four-wheel vehicle developed with the Lagrangian method. The random vertical and lateral undulations of the road surface have been accounted for in the analysis and represented by the Power Spectral Density (PSD) function. The vehicle ride is assessed based on the International Organization for Standardization (ISO) 2631-1 annexure and the vehicle overall ride index is determined. The vehicle’s vertical-lateral dynamics are evaluated based on a 1-8 hr comfort boundary laid in ISO specifications. In a further study, the vehicle inertial, suspension, and geometric parameters, which critically influence the vertical and lateral ride, have been identified. The vehicle’s vertical ride covers a relatively wide band of frequencies under the discomfort level of ISO comfort boundaries and is found to be more crucial as compared with the lateral ride; the recommendations are made to improve the vertical ride in preference. The total value of weighted Root Mean Square (RMS) acceleration of the vehicle determined from the present analysis is 2.47 m/s2, and the ride comfort index was found to be in the range “very uncomfortable” specified in ISO 2631-1 annexure. The present study provides a basis for the vehicle designer for the modification in the vehicle parameter values to obtain optimum ride comfort.
Sharma, Rakesh Chandmal, Vashist, Amit, Sharma, Neeraj, Singh, Gurpreet
Vibration Mitigation of Commercial Vehicle Active Tandem Axle Suspension System02-15-03-00151/24/2022
A tandem axle suspension is an important system to the ride comfort and vehicle stability of and road damage experience from commercial vehicles. This article introduces an investigation into the use of a controlled active tandem axle suspension, which for the first time enables more effective control using two fuzzy logic controllers (FLC). The proposed controllers compute the actuator forces based on system outputs: displacements, velocities, and accelerations of movable parts of tandem axle suspension as inputs to the controllers, in order to achieve better ride comfort and vehicle stability and extend the lifetime of road surface than the conventional passive suspension. A mathematical model of a six-degree-of-freedom (6-DOF) tandem axle suspension system is derived and simulated using Matlab/Simulink software. Control performance criteria such as vertical body acceleration (VBA), front suspension working space (FSWS), rear suspension working space (RSWS), front dynamic tire force (FDTF), and rear dynamic tire force (RDTF) are evaluated through bump and random road excitations to quantify the effectiveness of the proposed controlled active suspension systems. The simulated results indicate that the proposed controllers can provide a significant improvement in ride comfort and vehicle stability and minimize road damage over the passive suspension. The power consumption of the proposed controllers is evaluated and compared for both the front and rear axle. Finally, the designed FLC based on velocity and acceleration offers a superior enhancement of system vibration performance among all investigated suspension systems and needs less power.
Metered, Hassan, Ibrahim, Ibrahim Musaad
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
DEEP REINFORCEMENT LEARNING FOR SIMULTANEOUS PATH PLANNING AND STABILIZATION OF OFFROAD VEHICLES2024-01-39428/10/2021
ABSTRACT Motion planning algorithms for vehicles in an offroad environment have to contend with the significant vertical motion induced by the uneven terrain. Besides the obvious problems related to driver comfort, for autonomous vehicles, such “bumpy” vertical motion can induce significant mechanical noise in the real time data acquired from onboard sensors such as cameras to the point that perception becomes especially challenging. This paper advances a framework to address the problem of vertical motion in offroad autonomous motion control for vehicular systems. This framework is first developed to demonstrate the stabilization of the sprung mass in a modified quarter-car tracking a desired velocity while traversing a terrain with changing height. Even for an idealized model such as the quarter-car the dynamics turn out to be nonlinear and a model-based controller is not obvious. We therefore formulate this control problem as a Markov decision process and solve it using deep reinforcement learning. The control inputs that are learned are the torque on the wheel and the stiffness of the active suspension. It is demonstrated here that a time-varying velocity can be tracked with reduced chassis oscillations using these control inputs. We anticipate that reducing such oscillations will lead to sensor stabilization, which will improve perception and reduce the required frequency of recalibration. The deep reinforcement learning approach advanced in this paper remains useful for offroad motion planning when complex terramechanics and uncertain model parameters are introduced or the vehicle model increases in complexity. Citation: A. Salvi, J. Buzhardt, P. Tallapragada, V. Krovi, M. Brudnak, J. M. Smereka, “Deep reinforcement learning for simultaneous path planning and stabilization of offroad vehicles”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 10-12, 2021.
Salvi, Ameya, Buzhardt, Jake, Tallapragada, Phanindra, Krovi, Venkat, Brudnak, Mark, Smereka, Jonathon M.
Tire-Road Separation Time Reduction by an Adaptive Proportional-Integral-Derivative Controller Utilizing Particle Swarm Optimization Algorithm02-14-04-00335/5/2021
The article examines quarter-car dynamics with the possible separation of its tire from the road. A set of nondimensionalized differential equations has been proposed to minimize the involved parameters. Time and frequency response investigation of the system has been analyzed insightfully considering tire-road separation. To measure the separation of the tire, a time fraction index is defined, indicating the fraction of separation time in a cycle at steady-state conditions. Minimizing the index is assumed as the objective of the optimized system. An actuator is applied to the vehicle suspension in parallel with the mainspring and damper of the suspension. Particle Swarm Optimization (PSO) is used to properly tune a Proportional-Integral-Derivative (PID) controller for the active suspension system excited by a harmonic excitation. To verify the effectiveness of the control proposed, the controlled result compared with a passive suspension system illustrates the design, achieving a more comfortable ride with a significant decrease of the separation time.
Nguyen, Quy Dang, Milani, Sina, Marzbani, Hormoz, Jazar, Reza Nakahie
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