Browse Topic: Vehicle ride
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
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
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
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
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
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.
The return to Earth is a rough ride for astronauts, from the violent turbulence of atmospheric entry to a jarring landing. Hitting the ground in a Soyuz capsule is the equivalent of driving a car backward into a brick wall at 20 mph, and it’s resulting in more head and neck injuries than NASA computer models predicted. To collect more data, NASA’s Johnson Space Center in Houston commissioned a Small Business Innovation Research (SBIR) project to develop a wearable data recorder for astronaut spacesuits. One result, created by Diversified Technical Systems Inc. (DTS), is a miniature commercial device that now collects and transmits data for any application from airplane test flights to tracking high-value shipments.
The desert landscapes of the western United States have changed since Mr. Duke and Dr. Gonzo blazed a trail across them in a drug-infused haze. But their advice to buy the ticket and take the ride is still a wise mantra - especially in the serene comfort of a modern full-size pickup. As inhospitable as southern Nevada can be outside Sin City, the amenities within the climate-controlled and leather-lined cabin of the latest Ram pickups insulate you from those realities. SAE Media was invited to sample the latest heavy haulers in Ram's portfolio, including the new 2500 and 3500 models with the high-output version of the Cummins B6.7 diesel.
In the highly competitive automotive industry, optimizing vehicle components for superior performance and customer satisfaction is paramount. Hydrobushes play an integral role within vehicle suspension systems by absorbing vibrations and improving ride comfort. However, the traditional methods for tuning these components are time-consuming and heavily reliant on extensive empirical testing. This paper explores the advancing field of artificial intelligence (AI) and machine learning (ML) in the hydrobush tuning process, utilizing algorithms such as random forest, artificial neural networks, and logistic regression to efficiently analyze large datasets, uncover patterns, and predict optimal configurations. The study focuses on comparing these three AI/ML-based approaches to assess their effectiveness in improving the tuning process. A case study is presented, evaluating their performance and validating the most effective method through physical application, highlighting the potential
Ride comfort is an important factor in the development of vehicles. Understanding the characteristics of seat components allows more accurate analysis of ride comfort. This study focuses on urethane foam, which is commonly used in vehicle seats. Soft materials such as urethane foam have both elastic and viscous properties that vary with frequency and temperature. Dynamic viscoelastic measurements are effective for investigating the vibrational characteristics of such materials. Although there have been many studies on the viscoelastic properties of urethane foam, no prior research has focused on dynamic viscoelastic measurements during compression to simulate the condition of a person sitting on a seat. In this study, dynamic viscoelastic measurements were performed on compressed urethane foam. Moreover, measurements were conducted at low temperatures, and a master curve using the Williams–Landel–Ferry (WLF) formula (temperature–frequency conversion law) was created.
This recommended practice defines methods for the measurement of periodic, random and transient whole-body vibration. It indicates the principal factors that combine to determine the degree to which a vibration exposure will cause discomfort. Informative appendices indicate the current state of knowledge and provide guidance on the possible effects of motion and vibration on discomfort. The frequency range considered is 0.5 Hz to 80 Hz. This recommended practice also defines the principles of preferred methods of mounting transducers for determining human exposure. This recommended practice is applicable to light passenger vehicles (e.g., passenger cars and light trucks). This recommended practice is applicable to motions transmitted to the human body as a whole through the buttocks, back and feet of a seated occupant, as well as through the hands of a driver. This recommended practice offers a method for developing a ride performance index but does not specifically describe how to
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