Browse Topic: Vehicle ride
In recent years, the automotive industry has faced increasing pressure to accelerate development cycles and reduce costs. Simultaneously, ride comfort standards have risen due to the ongoing integration of autonomous driving functionalities. Consequently, it has become essential to ensure that ride comfort attains a high degree of maturity at the very early stages of the automotive development process. This necessitates the establishment of objective criteria that enable the reliable estimation of subjective ride comfort, utilizing simulation-based assessment methods. This study introduces a methodological framework designed to systematically translate the manufacturer specific subjective perception and assessment of ride comfort into objective descriptions using a dynamic driving simulator. The framework is conceived as a generic approach, enabling the comprehensive application to a wide spectrum of subjective ride comfort phenomena, while being specifically optimized for the challenges of the automotive industry. Employing this framework facilitates the derivation of highly detailed, objective descriptions of subjective ride comfort evaluations, which promotes the achievement of advanced ride comfort maturity for new vehicles in early development phases and supports the overall enhancement of ride comfort. The exemplary application of the framework to a transient, one-dimensional ride comfort phenomenon demonstrates its capability to derive robust objective models from subjective evaluations conducted with professional test drivers in a dynamic driving simulator environment.
Kenworth's new C580 vocational truck made its debut at CONEXPO 2026. The C580 is the replacement for the long-serving C500 and aims to build on that truck's legacy thanks to new tech, more muscle and improved interior amenities. According to Kenworth, the C580 rides on the C500 platform, but has been endowed with Kenworth's latest cab, which brings modern comfort and technology features. Truck & Off-Highway Engineering was in attendance for Kenworth's introductory press conference for the C580 in Las Vegas.
For Urban Air Mobility taxis, passengers will experience different levels of heave motion during flight. Researchers at NASA Armstrong Flight Research Center conducted two studies in which passengers were exposed to varying levels of heave motion in the Armstrong Virtual Reality Passenger Ride Quality Laboratory. In the first study, twenty-three volunteers from the Armstrong workforce evaluated the motions on a five-point rating scale and a binary comfort scale; in the second study, fifty volunteers evaluated a flight experience with varying levels of stimuli using a five-point comfort scale and a five-point passenger acceptance scale. This paper combines the results of these two studies to observe the relationship between heave motion and passenger rider quality and acceptance. Both passenger comfort and acceptance were found to decrease with increasing heave acceleration The statistically significant relationship between the magnitude of heave acceleration and passenger comfort for individual studies and combined results are discussed.
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.
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.
This paper presents an initial handling qualities analysis of an Electric Vertical Take-Off and Landing (eVTOL) hexacopter. The analysis uses the Distributed Electric Propulsion Simulation (DEPSim), developed by Penn State University (PSU) and the Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM), developed by Continuum Dynamics, Inc. (CDI). The study focuses on evaluating a generic AAM hexacopter performing Handling Qualities Task Elements (HQTE) as defined by the DOT / FAA. A trajectory controller was developed to enable simulation of prescribed flight paths, allowing automated simulation of four HQTEs: Heliport Approach, Hovering Turn and Hold, Pirouette, Lateral Reposition and Hold. Design modifications incorporating lateral mast tilt and Direct Side Force Control (DSFC) were implemented to enhance yaw control and ride qualities. Piloted simulations were conducted at the PSU rotorcraft flight simulation facility using DEPSim, employing an Attitude Command Attitude Hold (ACAH) architecture with mode switching to Translational Rate Command / Position Hold (TRC / PH) and TRC plus DSFC modes. Two of the four HQTEs were tested in piloted simulations. Though formal ratings were not collected at this time, pilot commands and performance indicated that TRC / PH and TRC plus DSFC modes enhance handling qualities over ACAH mode. The DSFC control law was found to have substantially reduced roll attitude, which could potentially enhance visual cueing, pilot comfort, and pilot-perceived handling qualities.
Nowadays, customers expect excellent cabin insulation and superior ride comfort in electric vehicles. OEMs focus on fine tuning the suspension system in electric vehicle to isolate the road induced shocks which finally offers superior ride quality. This paper focuses on enhancing the ride comfort by reducing the road excitation which originates mainly due to road inputs. Higher steering wheel vibration is perceived on the test vehicle on rough road surfaces. To determine the predominant force transfer path, Multi reference Transfer Path Analysis (MTPA) is performed on the front and rear suspension. Based on the finding from MTPA, various recommendations are explored and the effect of each modification is discussed. Apart from this, Operational Deflection Shape (ODS) analysis is used to determine the deflection shape on the entire steering system . Based on ODS findings, recommendations like dynamic stiffness improvements on the steering column and steering wheel are explored and the impact on the steering wheel vibration is discussed. With all the counter measures proposed, steering wheel vibration levels are reduced by ~ 7 dB . Component level modal targets are proposed to avoid the vibration concern due to road excitation.
The customer perception of ride comfort with vehicle performance is the most important aspect in a vehicle design. The ride comfort and vehicle performance are influenced by driveline components i.e. propeller shaft phase angle, inclination angle and critical frequency of the driveline system. The optimization of the driveline system is essential to ensure the efficient and smooth power transfer. Propeller shaft is one of the critical components in the driveline to influence the vehicle performance. Propeller shaft characteristics influenced by several factors like vehicle max torque, propeller shaft joint type, materials properties, UJ phase and inclination angle and shaft unbalance value. The optimization of the above parameter within the tolerance limit enables to meet the required performance standard. Various methodologies are available to optimize these parameters to enhance the vehicle performance and comfort leads to customer satisfactions. This study focuses on the analytical optimization of the propeller shaft’s universal joint (UJ) phase and inclination angle and validated at vehicle level. An analytical model was employed to evaluate the velocity fluctuations across the full rotation of the propeller shaft by considering the different UJ phase angles (0° − 360°) and inclination angles (1° − 5°). It was observed from the study that optimization of these parameter improves the vibration performance and decreases the velocity fluctuations. The results shows that the well optimized propeller shaft will enhance smoothness in the driveline systems, reduction in NVH levels, vehicle performance and ride comfort. This study suggests the importance of the precise geometry alignment in driveline design and provide the further refinement methodology.
This study presents an integrated vehicle dynamics framework combining a 12-degree-of-freedom full vehicle model with advanced control strategies to enhance both ride comfort and handling stability. Unlike simplified models, it incorporates linear and nonlinear tire characteristics to simulate real-world dynamic behavior with higher accuracy. An active roll control system using rear suspension actuators is developed to mitigate excessive body roll and yaw instability during cornering and maneuvers. A co-simulation environment is established by coupling MATLAB/Simulink-based control algorithms with high-fidelity multibody dynamics modeled in ADAMS Car, enabling precise, real-time interaction between control logic and vehicle response. The model is calibrated and validated against data from an instrumented test vehicle, ensuring practical relevance. Simulation results show significant reductions in roll angle, yaw rate deviation, and lateral acceleration, highlighting the effectiveness of the proposed approach. Overall, the framework offers a scalable and robust foundation for developing adaptive stability control systems in modern four-wheeled vehicles
The automotive industry constantly strives to enhance vehicle safety, comfort, and customer satisfaction. One of the critical aspects influencing these factors is the mitigation of Buzz, Squeak, and Rattle (BSR) issues, which can significantly impact perceived vehicle quality and user experience. This paper focuses on the BSR challenges specifically encountered in bench seat latch & striker mechanisms. Vibrations and movement, especially during vehicle operation, exacerbate Buzz, Squeak & Rattle (BSR) problems, leading to acoustic disturbances that detract from the overall ride quality. Latch and striker in seat system is prone to squeaks and rattles (S&R) due to improper fitment, environmental conditions, or mechanical stress. These issues not only compromise the auditory experience but may also raise concerns about component durability and functionality. This paper outlines the root causes of BSR phenomena in these components, emphasizing the role of design optimization, material selection, and assembly precision in addressing these challenges. By addressing these concerns, automotive manufacturers can ensure a higher standard of quality, reinforcing customer trust and satisfaction in their products.
Tire noise reduction is important for improving ride comfort, especially in electric vehicle due to lack of engine noise and majority of the noise generated in-cabin is from tire-road interaction. Therefore, the tire tread pattern contribution is one of the important criteria for NVH performance apart from other structurally generated noise and vibration. In this work a GUI-based pitch sequence optimization tool is developed to support tire design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. The key point to be considered in this pitch sequence is that it should be reducing the tonal sound and equally spread i.e., the same pitch cannot be concentrated on one side which may lead to non-uniformity. So, the restriction is that the highest and lowest pitch types cannot occur adjacent to one another. This design rule helps in reducing undesirable pattern non-uniformity and improves both acoustic and structural performance. This tool helps in faster design iteration and integration with downstream development processes. This tool is also validated in current OE projects showing promising improvements in tire noise behavior while maintaining realistic design feasibility.
Aluminum alloy wheels have become the preferred choice over steel wheels due to their lightweight nature, enhanced aesthetics, and contribution to improved fuel efficiency. Traditionally, these wheels are manufactured using methods such as Gravity Die Casting (GDC) [1] or Low Pressure Die Casting (LPDC) [2]. As vehicle dynamics engineers continue to increase tire sizes to optimize handling performance, the corresponding increase in wheel rim size and weight poses a challenge for maintaining low unsprung mass, which is critical for ride quality. To address this, weight reduction has become a priority. Flow forming [3,4], an advanced wheel rim production technique, which offers a solution for reducing rim weight. This process employs high-pressure rollers to shape a metal disc into a wheel, specifically deforming the rim section while leaving the spoke and hub regions unaffected. By decreasing rim thickness, flow forming not only enhances strength and durability but also reduces overall wheel weight. This study investigates and compares the mechanical properties of conventional GDC and LPDC cast alloy wheels with flow-formed counterparts, focusing on the rim region. Results reveal that the flow-forming process facilitates a 30% thickness reduction in the rim section. Furthermore, it leads to a slight increase in yield and tensile strength while significantly improving elongation in parallel to the flow-forming direction. The study also examines microstructural changes, including the deformation behavior of silicon dendrites [5].
Engineers have developed a next-generation wearable system that enables people to control machines using everyday gestures — even while running, riding in a car, or floating on turbulent ocean waves.
Vehicle electrification has introduced new powertrain possibilities, such as the use of four independent in-wheel motors, enabling the development of control strategies that enhance vehicle safety and drivability. The development of a model capable of simulating vehicle behavior is fundamental for control system design. A high-fidelity model takes into account several parameters, such as vehicle ride height, track width, wheelbase, and others, making it possible to evaluate the vehicle’s behavior and allowing for prior validation of the design, thus contributing to improved vehicle safety and performance. In this context, this study presents a lateral dynamic model of a Formula 4WD vehicle with in-wheel motors, enabling the simulation and analysis of the vehicle’s behavior in cornering maneuvers. To achieve this, the complete lateral model is developed using MATLAB Simulink as the platform, incorporating the semi-empirical Hans Pacejka tire model, calculating yaw moment, and analyzing forces to accurately describe the vehicle’s dynamics.
Single motorcycle accidents are common in Nagano Prefecture where is mountainous areas in Japan. In a previous study, analysis of traffic accident statistics data suggested that the fatality and serious injury rates for uphill right curves and downhill left curves are high, however the true causes of these accidents remain unclear. In this study, a motorcycle simulator was used to evaluate the driving characteristics due to these road alignments. Evaluation courses based on combinations of uphill/downhill slopes and left/right curves were created, and experiments were conducted. The subjects of the study were expert riders and novice riders. The results showed that right curves are even more difficult to see near the entrance of the curve when accompanied by an uphill slope, making it easier to delay recognition and judgment of the curve. Expert riders recognized curves faster than novice riders. Additionally, expert riders take a large lean of the vehicle body, actively attempted to ride on the inside corner, while that of novice riders was less. On the other hand, for downhill left curves, there was a tendency for delayed judgment of sharp curves, and riders were more likely to increase their speed. Also, the expert riders recognized curve curvature earlier and had a greater lean angle of the vehicle body than the novice riders, but there was no significant difference. From these results, the road alignment combination of uphill/downhill slopes and left/right curve has a significant impact on the risk of motorcycle accidents.
To say 2025 has been a bumpy ride for North American electric vehicle OEMs would be an understatement not heard since Jack Swigert informed Houston that Apollo 13 was experiencing a problem. However, despite a tariff tug of war, EPA upheaval and continually changing tax incentives, OEMs are pushing ahead with plans to electrify the commercial truck segment. In late August, ZM Trucks celebrated the grand opening of its U.S. headquarters and assembly facility in Fontana, California. Truck & Off-Highway Engineering was in attendance for the opening ceremony, which included the U.S. debut of the ZM8 Class 4/5 truck.
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