Browse Topic: Suspension systems

Items (3,725)
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
The corner module is an innovative design that combines drive, steering, suspension, and other vehicle structures into a single wheel unit. This achieves a high level of integration for chassis functions. A chassis built on this module can perform more complex movements. Suspension is a key part that decides how the vehicle moves. However, current suspension design approaches lack a systematic methodology for configuration synthesis and analytical verification for the multi-degree-of-freedom (multi-DOF) requirements of the corner module. This study introduces a new method for designing the corner module suspension based on the Position and Orientation Characteristic theory (POC theory). First, the type of suspension DOF is derived from chassis functional requirements by treating the required corner module motion as the target suspension DOF. Then, we decide the number of chains, links, and joints in the mechanism and perform configuration synthesis of suspension mechanism. Next, we combine the selected kinematic pairs and select suspension mechanisms that meet the requirements of suspension DOF. There are two steps of calculation in this process. In this study, the goal is to design a suspension with three links, two loops, and two degrees of freedom. Seven suspension mechanisms with specific loops and components were obtained using the proposed process. Finally, the paper presents the process of mechanism verification. Using the steering link and ground excitation as inputs, theoretical calculations and simulation analysis were conducted to verify that the mechanisms obtained meets the suspension design objectives. This proves that the POC theory-based method for creating multi-DOF suspension is effective.
Kong, WenkaiZhu, WenfengZeng, Zhixuan
The probe is an important component of the precision instrument. During the measurement process, the deformation of the leaf spring directly affects the accuracy of the displacement of the probe. There are many undetermined parameters for the leaf spring, and some parameters have a non-linear impact on the results. This paper proposes a firefly algorithm that combines penalty functions to solve the optimal solution of the objective function for multi parameter leaf springs. Through strategies such as normalizing mapping intervals, setting small populations between cells, and fine-tuning position update formulas, this algorithm quickly obtains the optimal parameters of the leaf spring, and compares it with the orthogonal experimental method to prove the feasibility of this method, providing a certain theoretical reference value for multi parameter solving.
Yu, JianghaoShi, ZhaoyaoSong, Huixu
This paper takes a seaplane as the research object, based on the roll damping commonly used in the field of ships, to carry out the applicability analysis and design technology research of the roll damping for the seaplane. A T-tail configuration was selected as the attachment. The design process involved sequentially selecting the horizontal stabilizer airfoil, designing the aspect ratio parameters, and determining the strut airfoil. Consequently, two T-tail design schemes with aspect ratios of 0.76 and 1.53 were proposed. Through the hydrodynamic performance analysis of the T-tail design installed on the seaplane, the advantages and disadvantages of the two T-tail designs in the wave environment are studied. The results demonstrate that the aspect ratio of the T-tail’s horizontal stabilizer directly affects the seaplane’s wave-induced motion response. The proposed design with a larger aspect ratio of 1.53 significantly reduces wave resistance and motion response across various conditions. In the case of a relatively small aspect ratio, the maximum pitching motion is reduced by 38.4%, and the maximum heave is reduced by 59%.
Jiang, TingPi, XufengHe, ChaoWen, ChangqingLi, Xu
Given the braking deviation of commercial vehicles, this paper discusses the influencing factors and uses Adams simulation software to accurately model the vehicle model due to the unreasonable match between the suspension system and the steering system. Through K&C analysis and dynamics analysis of the model, the root cause of braking deviation is identified, and the simulation method is used to quickly realize optimization and verification.
Yan, TangWang, JingxianSun, HongyangWu, Zhen
This paper proposes a Linear Quadratic Regulator (LQR) parameter optimization method based on Particle Swarm Optimization (PSO) to enhance the grab attitude controller for rotary crane systems, with the objectives of improving positioning accuracy and suppressing load swing. Lagrange’s equations are first used to create a nonlinear dynamic model of the rotary crane, which is then linearized around an operational point to produce a fourth-order state-space representation. Based on this representation, a dual-objective fitness function is created, employing the Integral of Time multiplied by Absolute Error (ITAE) as the performance index and assigning the swing angle error more weight. The important parameters of the LQR weight matrix are optimized using the PSO algorithm. A dedicated novel pre-compensation gain algorithm is then developed to solve the pseudo-inverse of an augmented matrix, thereby removing steady-state error. According to simulation results, the PSO-optimized controller greatly improves the anti-sway performance and positioning accuracy of the system by reducing the peak swing angle and settling time by 33.9% and 55.9%, respectively, as compared to the traditional LQR control.
Yao, YuleiXiang, Yang
The reliability verification of cargo door latches for civil aircraft requires a safe, accurate, and controlled method for simulating jamming failures in lab settings. We adopt a crank-rocker mechanism with a variable degree of freedom (DOF) to construct a novel jamming apparatus that may be dynamically constrained in order to meet this requirement. The apparatus maintains two DOFs when not in use, which permits the latch mechanism to move freely. Both the guiding shafts and the rotation shafts are simultaneously constrained for a jamming test, reducing the mechanism’s DOFs to zero. This operation creates a precise and passive lock that immobilizes the mechanism without the need for an active external load. This approach offers a more realistic simulation of the sudden jamming brought on by wear, foreign object intrusion, or manufacturing tolerances. A theoretical kinematic analysis is then conducted to calculate the mobility of the mechanism and determine the theoretical conditions and transition paths to reach the two functional states. Moreover, the apparatus implements a real-time computational model based on classical planar linkage force analysis and integrates a multi-sensor system. This model converts sensor data into the torques and jamming forces that are actually delivered to the latch. The findings demonstrate that the proposed design accurately simulates latch jamming conditions while allowing for real-time monitoring and quantification of important dynamic characteristics. Thus, by offering a dependable and effective verification solution for cargo door latches, the apparatus greatly improves testing safety and the value of the data gathered.
Ren, JieZeng, XiaohuQiu, XudongXie, Youshui
During the cold rolling process, when the rolling speed enters the acceleration stage, the rolling force often exhibits a linear decline accompanied by fluctuations. This leads to a decrease in the uniformity of steel strip thickness distribution, resulting in the failure of the outgoing strip to meet quality requirements in terms of shape and thickness. In this paper, a three-dimensional model of a six-high rolling mill is established using Abaqus, and the influence of gap control during the acceleration stage on strip shape is systematically investigated. By analyzing the relationship between rolling force and roll gap variations, a gap compensation strategy based on a dynamic stiffness model is proposed. Simulation results demonstrate that implementing gap compensation during the acceleration stage effectively improves the consistency of strip thickness, with significant reductions in both thickness range and standard deviation.
Tang, YingxinYan, ZhuwenCao, WenjunWu, Jiawei
This paper systematically optimizes and validates the handling stability of a vehicle using ADAMS/Car software based on vehicle data provided by a car manufacturer. A comprehensive vehicle dynamics model was established, including a body model, an anti-roll bar model, a powertrain model, a steering subsystem model, and a full vehicle model, with a focus on optimizing suspension parameters such as toe angle and camber angle. Validation was carried out using simulation test methods such as dual-wheel synchronous excitation, steering returnability, and angle step input. The results show significant improvements in the vehicle’s yaw rate, steering force, and torque after optimization, with particular excellence in steering return time and transient response. Additionally, steady-state cornering simulation results indicate that the optimized vehicle has improved body roll stiffness and lateral compliance, with increased understeer, further enhancing stability and response speed during steering. The findings of this study improve the handling stability and safety of vehicles and provide valuable references for future automotive design.
Li, DiannuoZhu, JialeWang, DongmeiWei, YiHuang, YuanyuanBan, Lu
The structural stiffness of a manned lunar vehicle is a core indicator ensuring its stable operation in the complex lunar environment. The vehicle’s body structure must meet multiple requirements, including high stiffness, lightweight design, and adaptability to lunar surface conditions. Since lunar gravity is only 1/6 of Earth’s and the terrain is rugged and dusty, the body structure must employ a high-stiffness design to withstand driving impacts and resist deformation, thereby preventing mechanical failures or safety hazards for crew members caused by excessive structural distortion. However, excessive structural stiffness would result in an overweight vehicle body, conflicting with the spacecraft’s lightweight requirements. Thus, the structural stiffness index should be optimized to a lower value while ensuring safe operation during lunar surface driving without compromising performance. This paper calculates and determines the structural bending and torsional stiffness indicators for the manned lunar vehicle’s body through simplified model calculation and the FEA method.
Shen, ZhenghuiWu, YingjiaYang, JianfengWang, WeijunZhang, ChongfengHan, Liangliang
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, SaisaiYang, ChangGuo, RuilingZhang, ZhongyuanLiang, DongWu, Shiyu
Advanced Driver Assistance Systems (ADAS) are increasingly prevalent in light vehicles, both in the United States and worldwide. Moreover, ADAS are steadily being incorporated into regulatory requirements globally. Like ADAS, the automotive aftermarket is also increasing in size and significance. As both ADAS and the aftermarket industry are growing, the effect of aftermarket modifications on ADAS functionality should be examined. However, there is very little information available in the public domain about the effect of aftermarket modifications on original equipment ADAS. This work is centered on a considerable research project that was conducted to address the knowledge gap at the intersection of ADAS and the aftermarket. The project investigates five light vehicles that are important to the aftermarket, including four pickup trucks and one sport-utility vehicle. It focuses solely on the effect of popular aftermarket suspension modifications, and it does not evaluate aftermarket ADAS equipment. Typical suspension modifications were applied to the test vehicles in five modification categories, including stock, lower kits, level kits, 3–4 in. lift kits, and 6 in. lift kits. Six ADAS test procedures were performed for the test vehicles, comprised of blind spot detection, crash imminent braking, lane departure warning, pedestrian automatic emergency braking, rear cross traffic alert, and traffic jam assist. The physical tests were developed based on National Highway Traffic Safety Administration (NHTSA) New Car Assessment Program (NCAP) written experimental procedures. Statistical hypothesis testing was performed for the purpose of determining if average measured dynamic responses varied in the modified vehicles compared to stock. The results show that vehicles modified with typical aftermarket modifications will likely retain their ADAS functionality, given the limitations of the small sample size of five vehicles. Vehicles with 6 in. lift kits are expected to exhibit greater variability in their dynamic responses compared to stock. Plans for future work and unanswered research questions are outlined, with the goal of advancing aftermarket ADAS integration and ensuring the safety and performance of modified vehicles.
Bastiaan, Jennifer M.Morales, LuisMuller, Mike
This study addresses the insufficient tractive trafficability of four-track unmanned amphibious tracked vehicles (UATV) in beach terrain by proposing an optimization strategy based on coordinated suspension height and hitch point adjustment. A mathematical model of vehicle drawbar pull was established to systematically analyze the influence mechanisms of vertical load distribution, suspension adjustment, and hitch point elevation on tractive trafficability. DEM-MBD coupling simulations revealed differentiated traction laws under sandy loam and clay conditions, particularly regarding track overlap effects. Results demonstrate that in sandy loam, rear-axle traversal over front-axle tracks reduces drawbar pull due to soil loosening, whereas track overlap enhances drawbar pull in clay through soil compaction. Nine suspension-hitch configurations were tested, validating optimization strategies: increased front-axle loading (Configuration a) in sandy loam and reduced front-axle loading (Configuration f) in clay. These configurations significantly improved tractive trafficability.
Chen, YaoyaoGao, XueWang, WenhaoXu, Xiaojun
Vehicle vibrations during precision instrument transport can cause damage and failure. Existing vibration isolators often lack reliability, mass production feasibility, and easy maintenance. In this paper, we design and analyze a quasi-zero-stiffness vehicle-mounted isolator with an inerter, decreasing dynamic stiffness while raising the effective mass. Theoretical, simulation, and experimental results show improved isolation performance, lower isolation frequency, and a broader isolation bandwidth.
Li, KaiLv, SiboSun, NingDai, Shijie
With the country’s economy and people’s consumption capacity increasing, railroad transportation tasks have become more and more frequent, and it is growing the demand for the transportation of high-value goods, fresh produce, etc. Compared with traditional Freight vehicles, express freight vehicles have great advantages in terms of carrying capacity, mobility, and transportation cost, but when it run at a speed of 160 km/h, it often occurs that failure of axle-box rubber springs, primary vertical dampers, secondary lateral dampers, anti-yaw dampers, and air springs. How to ensure the safety and stability of the train under suspension system failure conditions is a problem that needs to be solved during the design process. In this paper, through multi-body system dynamics software, a nonlinear dynamics model of lateral and vertical coupling of the vehicle system is established to analyze the influence of suspension system failure on the stability of 160 km/h express freight vehicles. The analysis results show lowering the operating speeds can meet the Ride Quality of the Vehicles in special conditions.
Gao, ZhixiongMa, KaiXiao, YanmeiChen, WeidongWei, XiaoSha, ChengyuBian, Huihui
Fifteen instrumented crash tests were performed using a 2005 Yamaha R6 motorcycle. Seven tests were performed with upside-down (USD) forks and eight tests were performed with standard forks. The 2005 Yamaha R6 provided a platform where both types of front forks could be interchanged. For all tests, the motorcycle was delivered into a concrete block at speeds varying between 5 and 23 mph. Seven tests were conducted at low speeds to determine the onset of permanent deformation. Eight tests were conducted at higher speeds to observe the wheelbase reduction of the motorcycle and its relationship to impact speed. This paper summarizes the data from these tests related to wheelbase reduction, impact dynamics, and post-impact movement, allowing comparison between two different suspension systems and historical datasets.
Lucernoni, AnthonyBoyd, DustyWahba, RonnyTaeuber, AndreStoner, JacobLaw, Trevor
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, GuoyingWang, XinyuWang, JiaqiZhan, XinwangBi, ChenxiaoCong, ShiqiHua, MinSun, TianjunGao, Zhenhai
Recent advancements in system-level NVH (Noise, Vibration, and Harshness) development methodologies have improved target cascading and enabled more efficient system-level optimization. Dynamic substructuring facilitates the virtual integration and modification of multiple subsystems and the prediction of changes in overall transfer functions. In practical automotive applications, advanced frequency-based substructuring has been applied to virtually modify system parameters, such as mass and stiffness, at multiple points in a target system, allowing prediction of the resulting effects and optimization of parameter changes without physical intervention. This study extends the methodology by introducing an enhanced substructuring approach capable of addressing not only basic parameter modifications but also large-scale structural changes. The proposed process involves identifying the characteristics of a base system assembly and a target subsystem, decoupling the subsystem from the assembly, incorporating structural modifications, and predicting the resulting transfer function changes. The method was validated through two complementary workflows: a fully experimental test-based workflow and a hybrid workflow. The test-based workflow demonstrated the reliability of substructuring operations, decoupling and coupling, by experimentally evaluating the base assembly, the original subsystem, and the structurally modified subsystem. The hybrid workflow replaced the experimental subsystem models with finite element models, thereby demonstrating the feasibility of substructuring numerical subsystem models with a physical system assembly. Together, these workflows are applied to one of automotive suspension subsystems, cross-member, which can establish the accuracy, flexibility, and practical applicability of the proposed method in supporting system-level NVH development and structural optimization.
Cho, MunhwanBoelens, JelleReichart, Ronde Klerk, DennisAhn, Jiho
By using a fully trimmed vehicle body as flexible body, imported through a Modal Neutral File (MNF), in a complete vehicle Multibody Dynamics (MBD) analysis, the simulation setup gets considerably closer to the test conditions compared to only using a linear Finite Element Method (FEM) approach. Since the MBD analysis includes gravity, rigid body modes of the vehicle and the nonlinear behavior of the wheel suspension, it brings the correlation between simulation and test to a new and more comprehensive level. As correlation criteria, the results of the so-called Multi Stethoscope (MSS) are used. The MSS captures the time history of distortion in all body openings and cross sections and enables a detailed stiffness evaluation of the body using the so-called Opening Distortion Fingerprint (ODF). The ODF gives the quasi-static response while the Operational Deflection Shape (ODS), which is another result of the MSS measurements, reflects the dynamic response. Apart from the different individual steps of this new correlation approach, the paper highlights the importance of considering Component Mode Synthesis (CMS) when embedding and evaluating a linear FE model of the fully trimmed body in the nonlinear MBD environment through an MNF. An example of CMS using the Craig-Bampton method shows the impact of the different parameters included in the CMS. Furthermore, a new graphical feature in combination with the ODS is presented which enhances correlation capability. Finally, an example shows how this new correlation approach can improve the simulation model of a newly developed robotaxi for Waymo.
Lindkvist, LisaOlger, EmmaPiiroinen, PetriKarypidis, JohnPena, MiltonBäcklund, JesperAppelgren, PeterMarberg, HenrikUgale, PravinWeber, Jens
Achieving favorable Noise, Vibration, and Harshness (NVH) and durability performance in vehicles requires sufficient static and dynamic stiffness of the Body-in-White (BIW). Virtual development of BIW performance targets during the early design stages is essential to minimize costly modifications in later phases. In the automotive industry, full-scale finite element models are widely used for this purpose, offering high fidelity and enabling comprehensive performance evaluations. However, their complexity and high computational cost limit their practicality for early-stage sensitivity and optimization studies. Beam-based models offer a faster alternative; however, conventional beam formulations based on Euler–Bernoulli or Timoshenko beam theories often fail to capture the complex deformation behaviors of thin-walled structures, which are typical of BIW designs. This typically results in poor correlation with detailed models unless artificial joint flexibility is introduced at structural connections. To address these limitations, this study proposes a hybrid modeling approach that combines Higher-Order Beam (HOB) elements with shell elements. HOB elements account for sectional deformation modes—such as warping and distortion—beyond standard translational and rotational degrees of freedom, enabling a more accurate representation of thin-walled member behavior. This work extends previous research by applying HOB theory to BIW modeling, including panel components such as the floor and roof. Comparative analyses with detailed 3D models demonstrate strong agreement, validating the accuracy and efficiency of the proposed method. The results highlight the potential of HOB-based hybrid models as reliable, computationally efficient tools for early-stage BIW design evaluation and layout optimization.
Kim, Jin HongGang-Won, Jang
When developing a vehicle, the overall body stiffness is an important parameter to be estimated for several automotive attributes. As a complement to the traditional experimental and computational static torsional stiffness assessment, an improved method has been developed to evaluate the body stiffness when driving the vehicle on a test track. This method, valid for both test and simulation, is called Opening Distortion Fingerprint (ODF) and uses the so-called Multi Stethoscope (MSS) to measure the dynamic distortion in each body closure opening and cross section. For evaluating the distortion, from both test and Multi Body Dynamics (MBD) simulation data, the Evaluation-line (E-line) method is used. The E-line method is a linear approach. Consequently, it is only valid in the absence of large rigid body rotations of the vehicle body. Therefore, to assess the validity of the ODF method, it is crucial to identify the frequency at which the distortion results become invalid due to rigid body rotations. To identify this frequency range, in an MBD simulation the total distance output parameter can be requested and used. But for a dynamic full vehicle test, it is a major challenge to measure the total distance. Several tests have been performed without success. To calculate this frequency range from test data, this paper presents a new approach. In this methodology two different signal processing methods (E-line and Diagonal) are combined. To check the validity of the new approach, full vehicle test data has been evaluated. In addition, a simplified beam lab experiment is presented, highlighting the difference between test and MBD simulation when measuring the distortion at large rotations.
Olger, EmmaLindkvist, LisaPiiroinen, PetriKarypidis, JohnPena, MiltonBäcklund, JesperAppelgren, PeterMarberg, HenrikUgale, PravinWeber, Jens
The rapid electrification of the automotive industry introduces new challenges in noise, vibration, and harshness (NVH). In particular, in a virtual prototyping phase of the e-vehicles development, the rubber mounts are often one of the key elements to be considered when analysing the structure borne noise contributions. Having an accurate experimental characterization of the mount dynamic stiffness curves is therefore very relevant. However, conventional mount characterization methods are often pushed to their limits, partly due to the use of stiffer bushings, and partly because the frequency range of interest is extended toward higher frequencies. When using inverse substructuring, the dynamic stiffness curves can be obtained from frequency response function measurements. The required test setup consists of excitations and responses, located on each side of the mount via dedicated fixtures. The measured frequency response functions are reduced into 6 degrees of freedom representation at the active and passive side of the mount using the classical virtual point transformation. This classical approach assumes the fixtures to behave rigidly. This assumption holds in the lower frequency range, but not anymore in the higher frequency range. In this paper, novel approaches to identify the dynamic stiffness are presented. Namely, an enhanced virtual point transformation that considers flexible fixtures modes is proposed. Those modes may be obtained via finite element modeling or from an experimental modal analysis. Alternatively, a hybrid framework leveraging high-frequency testing and simulation to develop a parametric finite element mount model is presented. The latter approach eliminates the need for fixtures. These methodologies are compared and validated on an automotive rubber mount.
Bianciardi, FabioForrier, BartMinervini, DomenicoBarbieri, MarcoJanssens, Karl
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, XiaojunZhang, HongZou, YiYe, LeiLu, YiChen, RuiZou, HantongWang, Yang
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, JinxinXiao, FengKe, YuanJin, Liqiang
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, ZhiyingLi, JeiZhu, AndingBai, XianxuLi, WeihanLi, Rui
To address the issues of significant slip energy dissipation induced by severe tire slip, degradation of vehicle control stability, and insufficient accuracy of vehicle speed tracking under low-adhesion road conditions, a torque coordination control strategy for dual-motor electric vehicles (DM-EVs) considering load transfer and slip energy dissipation is proposed. First, a vehicle dynamics model integrating suspension system dynamics and tire slip characteristics is developed, fully accounting for the influence of front-rear axle load transfer on the tire slip ratio. Next, founded on the energy dissipation mechanism of tire slip, a quantitative model for energy dissipation during tire slip is developed. Finally, a longitudinal coordinated control system for vehicles according to nonlinear model predictive control (NMPC) is introduced. By comprehensively considering the tire slip ratio and vehicle load distribution, multi-objective coordinated optimization of wheel torque is achieved. Simulation results under constant acceleration conditions on low-adhesion roads indicate that significant slip phenomena occurred in the wheels of both the without slip ratio controller and the PID controller, failing to achieve stable vehicle control. Simulation results in virtual traffic scenarios reveal that, compared to the other two controllers, the proposed controller exhibits significant reductions in key performance metrics: the RMS value of total tire slip ratio is reduced by 84.95% and 87.34%, total tire slip energy dissipation is reduced by 94.95% and 96.53%, and total tire wear volume is reduced by 93.78% and 95.71%, respectively. These results demonstrate the performance of the introduced control strategy.
Hou, YingmingLi, JieBai, Xianxu
The TiltRotor Aeroelastic Stability Testbed (TRAST) was developed to experimentally investigate whirl-flutter stability of tiltrotor aircraft. Previous wind-tunnel testing focused on configurations representative of current generation tiltrotors utilizing gimballed rotor hubs. The TRAST platform was also designed to support a hingeless rotor system to investigate whirl-flutter mechanisms representative of stiff proprotor configurations. This paper presents analytical whirl-flutter predictions for a hingeless rotor configuration of the TRAST model. Structural mode shapes derived from a NASTRAN finite-element model are combined with comprehensive aeroelastic analyses in CAMRAD II and RCAS. The results show that the dominant whirl-flutter mechanism differs from the gimballed configuration, with instability occurring through the wing in-plane mode rather than the wing vertical bending mode. Parametric studies examining rotor speed, pitch-spring stiffness, rotor flexibility, and diaphragm spring stiffness are conducted to evaluate the sensitivity of the predicted stability boundary. Results indicate that the hingeless configuration is significantly more stable than the equivalent gimballed configuration and exhibits different trends with rotor speed and structural stiffness. These predictions help identify configurations of interest for future wind-tunnel testing and provide insight into whirl-flutter mechanisms for hingeless tiltrotor systems.
Kreshock, AndrewCobb, BenjaminThornbrugh, Robert
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 ShehataJabeen, Syeda DarakhshanEl-Zomor, Haytham M.Tolba, MohamedElamy, Mamdouh I.
In order to improve the comfort performance in commercial vehicles, this study proposes a hierarchical control strategy that integrates the evaluation and migration of control algorithms. First, a quarter-vehicle model with four-degree-of-freedom (4-DOF) is constructed, incorporating the dynamics of the wheel, frame, driver’s cab, and seat. The key modal characteristics of the model are then verified through amplitude–frequency analysis, confirming their consistency with the typical vibration patterns observed in actual commercial vehicles, which provides the foundation for subsequent control strategy evaluation and migration. Then, based on a standard two-degree-of-freedom (2-DOF) suspension model, a weighted comprehensive evaluation function is developed to account for comfort, structural safety, handling stability, and both time- and frequency-domain performance indicators. Using this evaluation function, various control algorithms—including Skyhook control (SH), acceleration-based damping control (ADD), and proportional–integral–derivative control (PID)—are systematically assessed. The control algorithm is migrated to the 4-DOF model to carry out the hierarchical collaborative control. The results show that this method can effectively inhibit vibration transmission to enhance ride comfort and improve structural safety at the same time, while maintaining an acceptable level of handling performance. The transferability and applicability of the hierarchical control method are validated for the considered vertical dynamics scenarios. This article provides a new theoretical method and technical pathway for the comfort-oriented performance optimization of commercial vehicles.
Pan, TingPang, JianzhongWu, JinglaiZhang, JiuxiangKang, GongZhang, Yunqing
During the initial design phase, automotive Original Equipment Manufacturers (OEMs) require the adaptability to examine various suspension system architectures while maintaining focus on the specific performance objectives. Those requirements are expressed by Kinematics and Compliance (K&C) look-up tables and represent the footprint of what the suspension should look like in real-world applications. However, translating those requirements into the full geometric hardpoint layout is not straightforward. This process often relies on trial-and-error approaches, making it time consuming and requiring significant expertise. This challenge, known as ”target cascading,” remains a major hurdle for many engineers. The main objective of this paper is to cascade the suspension requirements from K&C look-up tables to hardpoint locations by adopting an automatic workflow and ensuring respect for constructive and feasibility constraints. Design space exploration was conducted using a robust optimization methodology leveraging a Reduced-Order Model (ROM) of a MacPherson suspension. Feasible designs are ensured by incorporating physical constraints such as roll center variation, scrub radius range, tie rod inclination, packaging limitations and relative hardpoint influence. The usage of ROM significantly accelerates the optimization cycle, reducing the computation time from 2 days to 3 hours.
Brigida, PieroDi Carlo, PaoloDi Gioia, NiccolòGeluk, TheoTong, SonAlirand, MarcGorgoretti, DavideOcchineri, MarcoTassini, NicolaBerzi, Lorenzo
The main purpose of this study is to develop and validate an accurate calculation model for a hydraulic damper piston valve joint, enabling reliable torque specification and clamp behavior without full prototype iteration. Joint stiffness is a primary interest point. The joint features a bolted interface with a laminated shim stack of many thin disks with varying outer diameters. Analysis of such joints are uncommon in literature, making it challenging to quantify the effects of load distribution, truncation, and surface contact effects between members. The proposed models discussed in this paper are based on frustum load distribution combined with annular-plate bending and elastic-foundation effects to capture the effects of washer cupping. Concrete outputs of the calculator include member load distribution, bolt and member stiffnesses, torque-to-preload relationships, and an external-load simulation that predicts when individual members lose clamp load. Detailed internal hydraulic flow through piston valve orifices and shim hydrodynamics are outside the present scope. For model correlation, axisymmetric finite-element analyses of contact pressure and joint compression were conducted, and a 30-sample torque-to-failure study quantified general joint behavior and friction characteristics. The proposed virtual development method allows early selection of joint geometry and torque specification prior to physical builds. The performance characteristics of a representative joint are presented, with simulation and experimental results that show improved preload prediction.
Dresen, GabrielVollmar, RaceRoy Chowdhury, Sourav
This paper presents a testing platform for the development of lateral stability control systems in independent motor electric vehicles (EVs). A 10 degree of freedom (DOF) vehicle simulation and a radio control test vehicle are constructed to enable controls validation scalable to full size vehicles. These vehicle simulations, or ‘digital twins’, have been widely adopted throughout the automotive industry due to their lower operating costs and ease of implementation. Virtual models are not perfect representations of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially true when testing safety-critical features such as stability control. As a result, a simulation environment working in conjunction with a test vehicle represents an optimal hybrid approach. In this work, a high fidelity vehicle model is constructed in the Matlab/Simulink environment. To capture the effect of suspension, the digital twin is capable of modeling all angular and linear degrees of freedom of the vehicle body. The vehicle model must also estimate wheel forces during high-sideslip maneuvers. The Pacejka Magic Formula is used for its accurate representation of tire behavior in highly transient driving scenarios. This vehicle model describes the behavior of a physical vehicle. For this purpose, a 1/5 scale radio controlled vehicle with independent rear wheel propulsion is designed and assembled. All physical parameters of the test vehicle required by the vehicle model are estimated through direct measurement or estimation through test maneuvers. Magic formula coefficients are estimated from GPS, inertial, and odometry measurements collected throughout defined test maneuvers. Vehicle model behavior is then benchmarked against the test vehicle. An S-curve maneuver is performed in simulation and experimentation to ensure accuracy and consistency across transient and steady state behavior. In future work, focus will turn to creating an ADAS control system which re-stabilizes a vehicle after a collision using torque vectoring.
Petersen, Nicholas ConnerRobinette, Darrell
A suspension system was designed, fabricated, and tested following a systems design approach by an SAE Off-road Team from a North Midwest university. Compared to previous suspensions, the new suspension system is more reparable and contains a minimal number of custom parts, while still maintaining sufficient strength to withstand dynamic loads experienced when operating the vehicle. Modifications were also made to fit the newly designed vehicle body frame. As an integral part of the team’s 2025 Baja vehicle, the redesigned suspension system contributed to the vehicle’s improved performance during the 2025 SAE (Society of Automotive Engineers) Baja Competition. This paper presents a detailed account of the design, development, and fabrication process of the suspension system. The final design was tested and evaluated via both computer simulations and physical tests, whose efficiency and reliability were finally demonstrated by the team’s improved ranking in the 2025 Baja SAE Competition.
Liu, YuchengAnderson, MatthewLarson, CodyRodgers, JoshuaSeberger, AaronLetcher, Todd
The tire model is a crucial component in the design of the K-characteristic of FSAE racing car suspensions, and directly influences the achievement of maximum cornering lateral force. Not only do the slip angle, vertical load, tire pressure, and camber angle affect the mechanical characteristics of the tire, but temperature is also an important influencing factor when FSAE vehicle tires operate at high speeds. However, the modeling process of traditional tire models based on temperature characteristics is often very complex. The FSAE tire test code (FSAE TTC) already has a large amount of official sample data, which provides a basis for data-driven neural network models. This study implemented a hybrid modeling methodology, constructing two cascaded feedforward neural networks that combine the physical interpretability of the Magic Formula tire model with the nonlinear approximation capabilities of neural networks. The first network model uses slip angle, vertical load, tire pressure, and camber angle as input features, while the second uses tire temperature, ambient temperature, and ground temperature. The first network model simulates the magic formula model of the tire, and the second fine-tunes the lateral force, aligning moment, and overturning moment based on temperature characteristics. It prevents secondary input features (such as temperature) from being completely dominated by primary input features, facilitating the explanation of the influence of the two feature groups on tire characteristics. The accuracy and robustness of the model are suitable for the engineering requirements of FSAE. During the Formula Student China competition, based on on-track measured data, the tire model was co-simulated with VI-CarRealTime to quickly calculate the tire pressure required to achieve maximum lateral force. This effectively saved practice time before the race and helped the team achieve a third-place finish.
Liu, XiyuanWang, ShenyaoLi, MingyuanHuang, Jiayu
Parking assist systems are among the most widely adopted driver-assistance features in modern vehicles. A key component of these systems is the path planning module, which ensures accurate vehicle alignment within a parking slot while satisfying various constraints such as maintaining slot centering, avoiding collisions in confined spaces, minimizing maneuver count, and achieving the shortest feasible path. Multiple path generation techniques—such as geometric, polynomial-based, and search-based methods—have been developed to enable safe and efficient parking maneuvers. However, most of these approaches rely on the simplifying assumption that the vehicle’s instantaneous center of rotation (ICR) is fixed, typically located on the non-steering axle. In practice, the ICR is not constant and can vary significantly across vehicles due to several physical and kinematic factors, including steering geometry, tire slip characteristics, suspension configuration, and weight distribution. Neglecting these variations can introduce trajectory inaccuracies, reducing the precision and reliability of automated parking systems. Although prior studies have explored estimation methods for the instantaneous center of rotation (ICR), limited research has examined how variations in the ICR influence overall parking performance. This paper addresses this gap by investigating the impact of ICR variation on path generation and motion control accuracy in parking assist systems. A simulation-based study using an SUV-class vehicle model is conducted to evaluate system behavior across diverse parking scenarios. The results demonstrate how ICR assumptions affect path precision and overall parking accuracy, providing insights to enhance path planning and control algorithms for real-world applications.
Awathe, ArpitPatanwala, AbizerJain, ArihantVarunjikar, Tejas
This article deals with the development of a real-time capable, three-dimensional model of the Mercedes-Benz G-Class with flexible ladder frame that considers nonlinear suspension kinematics and force elements. The shift to new drivetrain technologies often results in a significant increase in vehicle weight and requires corresponding design modifications – also applying to off-road vehicles. These modifications result in changed stiffness of elements such as the ladder frame or anti-roll bar, which significantly affect vehicle dynamics and off-road performance. Therefore, strategic, efficient assessments must be made in early development stages, where no detailed information about individual systems and components is available yet, to detect and avoid potential massive, costly changes in later stages. This requires a “handmade” vehicle simulation model specifically tailored to this particular application, since the use of commercial multi-purpose simulation packages is not effective or suitable in this highly problem-oriented case. Based on a rigid multibody system approach and principles of analytical mechanics, the equations of motion of this novel model are derived in their mathematically most efficient form and implemented in MATLAB/Simulink. The complete system is separated into a modular structure of subsystems to enable efficient numerical solving of the complex overall system as well as easy modifications of certain characteristics or whole subsystems such as frame, body, wheel suspensions, and tires. All couplings are modelled by appropriate force elements or kinematic constraints. The parameter identification process is described and an experimental validation of the vehicle model based on measurements of the Ramp Travel Index (RTI) is presented. The results show that the model enables numerically efficient and physically plausible assessments with sufficient accuracy. Finally, an outlook and recommendations regarding further investigations are given.
Riebler, SandroPernsteiner, SamuelGranitz, ChristinaSchabauer, Martin
This paper presents a hybrid optimization framework that integrates Multi-Physics Topology Optimization (MPTO) with a Neural Network–surrogated Design of Experiments (NN-DOE) to enable lightweight structural design while satisfying crashworthiness, durability, and noise, vibration, and harshness (NVH) requirements under practical casting and packaging constraints. In the proposed MPTO formulation, crash and durability performances are incorporated through equivalent static compliance measures, while NVH performance is assessed using a frequency-domain dynamic stiffness metric, allowing consistent evaluation of trade-offs among competing design requirements. The framework is first demonstrated using a mass-produced passenger-car lower control arm (LCA) as a benchmark component. In this application, MPTO achieves weight reduction under multi-physics objectives by removing non-load-bearing material. Results show that single-discipline optimization produces unbalanced topologies, while balanced crash–durability–NVH consideration yields robust load paths. The study further demonstrates that crash and durability are dominated by static compliance–based response, whereas NVH performance is governed by frequency-dependent dynamic response over the relevant frequency range. The framework is then applied to a front engine mounting bracket of a newly developed heavy-duty truck. In this second application, a two-step strategy is employed in which MPTO first establishes the global load-carrying topology under manufacturing and packaging constraints, followed by NN-DOE–based local refinement to achieve stress attenuation at non-designable regions through global structural stiffness rebalancing, rather than direct geometric modification. Final verification confirms a steel-to-aluminum material transition achieving approximately 45% weight reduction and a substantial improvement in durability fatigue life, while maintaining required crash performance.
Kim, HyosigSenkowski, AndresGona, KiranSaroha, LalitBoraiah, Mahesh
Tuned Mass Dampers (TMDs) are widely used in the automotive industry to mitigate Noise, Vibration, and Harshness (NVH) issues across various vehicle systems. These passive devices are particularly effective in reducing structural vibrations in components subjected to resonant excitation. However, real-world applications often face challenges due to manufacturing variability and system-level build differences, which can cause deviations in both the TMD’s tuned frequency (up to ±15%) and the vibration characteristics of the host structure. These uncertainties—in both the TMD properties and the vehicle subsystem dynamics—can be modeled using statistical distributions. This paper presents a generalized methodology for vibration analysis and design under uncertainty, combining reliability engineering with dynamic vibration modeling. The approach formulates a unified mathematical framework that incorporates probabilistic and stochastic modeling to assess TMD performance under a range of build and environmental conditions. As a case study, the method is applied to assess steering column vibrations, with a focus on quantifying the probability that system performance meets specified NVH targets. Multiple statistical distribution models are considered to predict the likelihood that vibrations exceed customer acceptance thresholds, potentially leading to unfavorable subjective and objective ratings. The results are validated using population-level vehicle data. While demonstrated on the steering system, the proposed methodology is applicable to any vehicle subsystem equipped with a TMD, provided that the relevant random variables—such as modal properties, excitation inputs, and build tolerances—are properly characterized. This enables robust TMD design across vehicle domains, ensuring performance consistency despite system variability.
Abbas, AhmadHaider, Syedd'Souza, Suneel
Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving beyond traditional durability methods that do not model a range of real-world usage behavior. The study has been conducted using one instrumented vehicle (RLDA) and de-identified telemetry data from over 20,000 Rivian customer vehicles. The study analyzes the impact of variations in ride height, damper stiffness of active dampers, and roll stiffness of the suspension on vehicle structural durability. By combining usage frequency of the different settings with the damage accrued in these settings, the methodology estimates the high-cycle fatigue pseudo-damage variation for a wide range of customers and compares real world damage risk with the damage accounted for in the baseline durability testing. Through the analysis, we recommend a way to optimize the Accelerated Duty Cycle (ADC) for Over the Road (OTR) testing to minimize real-world risk, while keeping the duty cycle simple and practical for testing, i.e., test for an optimized combination of a few dominant settings and not a wide range of settings. The approach also suggests a path to a real-time fleet monitoring system to identify high-durability-risk customers and develop mitigation strategies.
Demiri, AlbionRamakrishnan, SankaranWhite, DylanKhapane, PrashantBorton, Zackery
Vehicle pull under acceleration is a phenomenon commonly observed in high-performance vehicles and electric vehicles (EVs), primarily arising asymmetric driveshaft angles, drivetrain architecture, and suspension geometry. In addition to these mechanical factors, tire characteristics, particularly the tire lateral force generated at the contact patch, significantly influence this effect. The lateral force is intricately tied to the dynamics of the contact patch and the geometric design of the tire tread pattern. This study investigates the relationship between tread pattern geometry and vehicle pull under acceleration, emphasizing the role of tire lateral force variations. By employing finite element (FE) simulation, lateral force response variations (dfy/dfx) resulting from tread block deformation were analyzed. Based on these simulation, a robust analytical methodology for tread pattern evaluation and optimization was established. The developed tread pattern characteristic parameter was validated through a thorough comparison between physical testing and FE simulation results, demonstrating high consistency. Vehicle-level testing further confirmed that the application of the optimized tread pattern design significantly reduced vehicle pull under acceleration. Moreover, performance criteria for tire lateral force were defined based on the maximum torque and output requirements of high-performance and electric vehicles. The study concludes that implementing the developed tread pattern characteristic parameter enables the design of tires with enhanced resistance to vehicle pull under acceleration. Such advancements are poised to enhance steering stability, handling performance, and overall safety in vehicles with high torque outputs, especially EVs and high-performance models.
Yoon, YoungsamJang, DongjinKim, HyungjooLee, Jaekil
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, ZhehuiZhang, LijunMeng, DejianHu, Xingyu
Helical compression springs have been used widely in various industries from automotive, aerospace and construction to electronics and medical devices. In the automotive industry, they appear in many places such as suspension, valvetrain, etc., as well in the discharge check valve of Gasoline Direct Injection (GDI) pump, which is the subject of study due to a recent fracture in lab testing. A theoretical study is conducted first to establish the equation governing spring dynamic motion under impact velocity, which can be in high magnitude with surging shock wave along spring axis. A new spring shock wave equation is developed for spring axial motion coupled with coil torsional effect. This newly derived shock wave equation has a broader term than the classic spring formula found in most engineering books. In this paper, it shows that the classic spring shock wave equation is only a special case for the general wave equation newly discovered. Then, a theoretical formula on spring shock wave propagation speed and natural frequency are presented, validated by a numerical simulation result by FEA on the spring natural frequency. Next, a FEA tool is employed to study the spring system under transient impact velocity, the spring dynamic stress at fracture location is obtained. It compares closely with the analytical approximate solution. Finally, a fatigue life assessment is performed, back up by the fractured part photo as well as the fatigue life cycles observed in testing. They are found in good agreement.
Pang, Michael L.Gunturu, SrinuNorkin, Eugene
With the rapid development of automated driving and the increasing adoption of “zero-gravity” seats, the crash safety of highly reclined occupants has become a critical issue. The current THOR dummy, designed for frontal impacts in the standard upright posture, exhibits limitations when directly applied to reclined seating configurations, including insufficient spinal flexion capability and excessive posterior pelvic rotation. In this study, the thoracolumbar spine kinematics of the THUMS human body model, reconstructed against post-mortem human subject (PMHS) tests, were analyzed. A two-segment linear fitting was employed to characterize a “dummy-like” spinal flexion response, yielding a virtual rotational hinge located near the thoracolumbar joint of the original THOR model. The characteristic rotation angle obtained from THUMS showed a strong linear correlation with the flexion moment of the T12–L1 vertebrae. Based on this relationship, the rotational joint of the THOR dummy was unlocked during impact and assigned a torsional stiffness of 600 Nm/rad. Additional modifications were implemented in the hip region to enhance model applicability. Comparative simulations demonstrated that the modified THOR model achieved closer agreement with PMHS responses than both the Hybrid III and the baseline open-source THOR models. In particular, the posterior pelvic tilt was reduced from approximately 20° in the baseline THOR to about 10° in the modified version. These results indicate that incorporating PMHS-based thoracolumbar flexion characteristics together with targeted hip modifications significantly improves the biofidelity of the THOR dummy for reclined-occupant crash scenarios, providing a solid foundation for future dummy development and safety assessment.
Guo, WenchengKuang, GaoyuanShen, WenxuanTan, PuyuanZhou, Qing
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, FlorianArmengaud, EricFormento, CeciliaMoscone, GiuliaSorrentino, GennaroBisciaio, GiorgioSorniotti, AldoAmati, NicolaBraun, DanielDeibler, BerndBoxberger, ValeriusSottile, SalvatoreIvanov, ValentinFuse, HiroyukiKompara, Tomaž
When a vehicle performs planar motion, the tire side force induces a jacking-up effect determined by the suspension roll center height governed by suspension geometry. These jacking forces also excite pitching motion. In this study, the pitching degree of freedom, along with roll degree of freedom, was incorporated in the bicycle model of the vehicle motion, hence it becomes four-degree-of-freedom model, and a new analytical method that applies modal analysis method to the model decomposes the motion of the sprung mass of the vehicle into mutually independent vibration modes. Since the superposition of these vibration modes can reproduce vehicle motion, these vibration modes are the fundamental factors governing sprung-mass behavior. Therefore, understanding how these vibration modes respond to design parameters provides a theoretical foundation to design desired vehicle dynamics from the early stage of car development. This report presents, by conducting modal analysis of the four-degree-of-freedom model, that the pitching dominant mode and the mode associated with planar motion and roll, which constitute a three-degree-of-freedom system, are mutually independent dynamically. Furthermore, the suspension design method that controls the pitch-dominant mode can ameliorate the initial turn-in response of the sprung mass in the desirable direction. The insight presented in this report can offer a systematic understanding of the essential characteristics of sprung mass dynamics and can provide new theoretical framework for vehicle dynamics performance design.
Kusaka, KaoruYuhara, TakahiroKoakutsu, Shingo
In recent years, premium vehicles have increasingly incorporated suspension systems capable of adjusting ride height. The primary function of these systems is to enable the vehicle to traverse uneven terrain by elevating the chassis, thereby preventing contact between the underbody and the road surface. Notably, air spring-based mechanisms enhance ride comfort by modulating the wheel rate. The system proposed in this study achieves ride height adjustment through vertical displacement of the spring’s lower seat. By constructing a detailed mechanical topology model using a dynamic simulation tool, this research aims to evaluate the feasibility of improving driving performance not only through height regulation but also by actively controlling the vehicle’s posture during motion.
Park, JaeyongSang Hoon, LeeJong Min, KimChoi, Jang Han
The performance of chassis suspension mechanisms critically affects vehicle handling, ride comfort, and safety. Implementing real-time health monitoring for chassis systems contributes to preventing severe consequences such as increased body roll or loss of handling stability caused by shock absorber softening or spring stiffness degradation under deteriorating operating conditions, while circumventing the substantial costs associated with professional facility-based chassis inspections. With the rapid development of sensing and data analytics technologies, data-driven approaches are increasingly used in health monitoring. This study aims to achieve online monitoring of chassis suspension performance degradation using a deep neural network (DNN). First, a half-car model incorporating both vertical and pitch motions was established to simulate bumpy road conditions, with the aim of constructing a dataset that includes key vehicle suspension parameters and vehicle states related to their degradation characteristics. Subsequently, a DNN model comprising three hidden layers is developed to assess suspension performance degradation. To optimize model performance, the effects of different numbers of neurons and hidden layers on model accuracy are explored. Experimental results show that the maximum absolute percentage errors of the DNN model in predicting suspension stiffness and damping coefficients are less than 0.13% and 0.17%, respectively, with average absolute percentage errors below 0.046% and 0.06%. The coefficients of determination (R2) exceed 0.999. The proposed method accurately predicts the trend of key suspension parameters, providing robust data support for health management and maintenance decision-making. This is expected to reduce safety risks and maintenance costs while enhancing overall vehicle performance and reliability.
Liao, YinshengLei, YisongSu, AilinWang, ZhenfengShi, ShuaiZhang, LeiZhang, JunzhiMa, Changye
Passenger comfort is becoming the forefront of luxury private jets where noise needs to be kept to a minimum. One source of structure-borne noise is the vibration of the Passenger Service Unit (PSU) panel. These vibrations originate from the outer skin, excited by turbulent boundary layer, and are transmitted through the fuselage frame to the PSU panel. This panel resides overhead of passenger seating, it is composed of a corrugated honeycomb core sandwiched between thin face-sheets. This paper presents a systematic approach to improve the vibro-acoustic performance of a honeycomb core sandwich structure by employing core filler and facesheet patches. Topology Optimization (TO) is used to determine the optimal layouts of these design modifications. The vibro-acoustic performance of the PSU panel with facesheet patches and core filler is evaluated using a frequency response analysis in the commercial finite element solver OptiStruct. The effectiveness of vibration reduction will be quantified by using the Dynamic Stiffness (DS) and velocity response of the PSU panel measured using the Frequency Response Function (FRF). Validation used excitations from 500 to 3000 Hz and indicated that using the TO interpreted layout of core filler and facesheet patches, separately improved the DS of the panel by 402% and 198%, and the velocity response by -35% and -18%, while increasing the weight by 0.1% and 4.7% respectively. Their combined effect has also been tested and found to provide an additional 445% improvement to DS and a -39% improvement in velocity response with 4.8% of additional material, though overall behavior varies depending on frequency range.
Russo, ConnorWhetstone, IsobelPatel, AnujWotten, ErikKim, Il Yong
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, ZhenhaiZhang, HanyingChen, GuoyingZhang, SuminHan, Zongzhi
To address the rollover risk of six-axle semi-trailers due to their large mass, high center of gravity, and multi-axle articulation, a lateral force balance anti-rollover strategy based on the Ackermann steering principle is proposed. By establishing the wheel angle constraint equations for the full-wheel steering system of the six-axle semi-trailer, a rigid-body dynamic model considering the articulation characteristics is developed. The key control and observation parameters are included in the wheel angles, center of gravity lateral offset, yaw angular velocity, sideslip angle, and lateral load transfer rate. An SMC-PID joint controller is designed, in which the third axle steering angle of the tractor is optimized by the SMC controller, and the trailer’s three-axle steering angle tracking control is achieved by the PID controller. The nonlinear accumulation of centrifugal force and dynamic load transfer under high-speed emergency lane change conditions is suppressed by a hierarchical control mechanism. The joint simulation results from TruckSim and Simulink indicate that, under the double lane change scenario with 88 km/h, the lateral force balance strategy reduces the rollover angles of the tractor and trailer by 85.5% and 86.9%, respectively, and the center of gravity lateral offset is improved by 77.5% and 92.3%; under the double lane change scenario with 80 km/h, compared with the active steering strategy of the trailer, the lateral load transfer rate fluctuation is reduced to the percentile level, and the rollover angles decrease by 62.9% and 65.3%.
Zhang, QiyuanZhang, LeiLiao, ShengkunSun, JinxuHe, Jing
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