Comfort Of Vehicle Research Articles

Evaluation of Road Roughness and Vehicle Speed Effects on Vibration Comfort of School Bus Driver Seats following the ISO 2631-1 Standard and Occupational Health and Safety Legislation

Human perception in terms of vehicle comfort problems is a significant issue for automotive manufacturers and academic researchers as evident from scientific papers available in the literature. In this study, the maximum vehicle speed is predicted for comfortable driving of school bus drivers at certain working conditions. First, a full-vehicle school bus model, which consists of a seat, vehicle body, wheels and suspension systems, is developed to evaluate vehicle seat comfort in accordance with International Organization for Standardization (ISO) 2631-1 and Occupational Health and Safety (OHS) legislation. Second, collected experimentally power spectrum densities of road roughness are converted to amplitude form in order to be an input to the developed full-vehicle model. Third, the frequency weighting factor, which is determined by International Organization for Standardization 2631-1, is applied to the calculated RMS acceleration of the seat. Finally, frequency-weighted RMS accelerations of the seat for various conditions of road roughness and vehicle speeds are obtained, and it is used to evaluate the bus driver seat comfort in accordance with ISO 2631-1. In addition, RMS accelerations of the bus driver seat are used to evaluate vehicle seat comfort in accordance with OHS legislation. It is concluded that the effects of vehicle speed and road roughness on comfortable driving are observed and maximum vehicle speed for comfortable driving decreases as the power spectrum density of road roughness increases. According to the results, measures to be taken in accordance with the OHS legislation are suggested.

Integrated optimization of the in-wheel motor driving system considering the ride comfort of the electric vehicle under multiple operating conditions

In this paper, a multi-objective optimization scheme integrating structural parameters with control parameters is proposed to address the adverse effects of an unbalanced magnetic pull of the wheel motor on vehicle dynamics. Firstly, the unbalanced magnetic pull under the air gap eccentricity of a switched reluctance motor is analyzed using both Maxwell’s stress method and the principle of virtual displacement. Then, a current chopper control strategy for the in-wheel motor is developed, and the influence of relevant control parameters on the output characteristics of the motor driving system under different driving conditions is discussed. Finally, a multi-objective optimization model of a motor under multiple operating conditions is developed with the aid of multidisciplinary optimization software. Integration of structural and control parameters for optimization. The results show that the motor design parameters determined by the integrated optimization scheme can improve the vehicle’s response characteristics under a wide range of operating conditions. In particular, the negative effect caused by an unbalanced magnetic pull during the operation of the vehicle is greatly suppressed.

Optimization and analysis of Sic reinforced copolymer blend composite structural springs

The design of lightweight leaf springs plays a crucial role in reducing fuel consumption and improving vehicle comfort by minimizing road shock transmission and vibration. Composite materials have shown great potential in significantly reducing leaf spring weight. epoxy, being a desirable thermoset polymer widely used in various applications such as electrical devices, ships and automobiles, exhibits limitations in terms of brittleness, fracture resistance and impact strength. To overcome these drawbacks while preserving its beneficial properties, epoxy can be blended with other polymers and reinforcements. In this study, polysulfide (PS) was selected as a suitable solution to enhance epoxy brittleness, offering an effective yet underutilized approach. Furthermore, the incorporation of silicon carbide (Sic), known for its superior characteristics, aimed to further enhance the mechanical properties of the epoxy-PS copolymer blend. The microstructural analysis was inspected using Fourier transform infrared. The blending and reinforcement process followed a Taguchi L8 static design to evaluate the impact of different composite blending percentages (represented as input factors) on leaf spring tensile strength, damping properties, impact resistance and hardness (represented as responses). The responses were analyzed using S/N ratios, ANOVA, main effect plots and interaction plots, while regression equations were employed to predict the responses under varying factors. The analysis demonstrated a robust model for manufacturing leaf springs. Experimental results indicated a 7.4% reduction in hardness with the addition of PS polymer. Conversely, reinforcing the epoxy-PS copolymer with 10–20% wt. of Sic resulted in a 3–5% increase in hardness. The natural frequency of the composite exhibited a gradual decrease upon the incorporation of PS and Sic. Evaluating the damping ratio revealed that the maximum value was achieved when the epoxy-PS copolymer was reinforced with 20% Sic. Additionally, while the copolymer blend displayed the greatest logarithmic decrement, epoxy exhibited the highest damping frequency.

The prospect of chassis structure design for new energy battery electric vehicles

More focus has been placed on creating new energy cars that are safer and more energy-efficient due to the development of new energy vehicle technologies and their strategic importance in addressing current energy and environmental issues. The chassis system's primary components, whether for a conventional fuel vehicle or a new energy vehicle, are the braking, suspension, and steering subsystems. The functioning, comfort, and safety of modern energy vehicles are strongly correlated to their structural design. At the moment, the design of new energy vehicle chassis is mostly based on refining and adapting the chassis of conventional fuel vehicles. However, new energy vehicles have distinct driving systems compared to conventional vehicles. Thus it is important to account for these variations in the layout and make it compatible with the whole system. The chassis structural design of new energy cars is more adaptable and affects vehicle performance compared to fuel-powered vehicles. The integrated battery and high amount of unsprung mass affect the center of gravity and stability of the new energy vehicle. The coordination and collaboration between the power battery module and the chassis construction must therefore be carefully considered, as well as their effects on the entire vehicle performance, including its safety and economic effectiveness. In conclusion, thoroughly examining the chassis structure design plan for new energy vehicles is crucial for advancing these vehicles.

Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO

There is no doubt that traffic noise has become one of the main sources of urban noise, and the electric bus, as an important means of transport frequently used by people in daily life, has a direct impact on the psychological and auditory health of passengers due to its interior noise characteristics. Consequently, studying electric bus sound quality is an important way to improve vehicle performance and comfort. In this paper, eight electric buses were selected and 64 noise samples were measured. Acoustic comfort was taken as an evaluation index, professionals were organized to complete the subjective evaluation tests for all noise samples based on rank score comparison (RSC). And nine psycho-acoustic objective parameters such as loudness, sharpness and roughness were calculated using ArtemiS software to establish the sound quality database of electric buses. Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost and PSO-XGBoost through data training. Finally, the calculation results of three indexes of average relative error, square root error and correlation coefficient indicate that the proposed PSO-XGBoost model is significantly better than GS-XGBoost and standard XGBoost, with its prediction accuracy as high as 97.6 %. This model is determined as the evaluation model of interior acoustic comfort for this case, providing a key technical support for future sound quality optimization of electric buses.

Considering cut-in behavior in mixed traffic: A longitudinal potential field-based car-following model for autonomous vehicles

To assure safety and comfort for autonomous vehicles (AVs) in the mixed traffic environment, a longitudinal potential field-based car-following model considering the cut-in behavior from an adjacent vehicle is established in this study. The longitudinal potential field (LPF), which includes the cut-in potential field, the hazard potential field and the velocity potential field, is constructed to quantitatively characterize the influence of the surrounding environment on the AVs. The cut-in potential field is created to indicate the possibility of cut-in behavior from the adjacent vehicle, the hazard potential field is intended to depict the risk of colliding with the preceding vehicle, and the velocity potential field is created to show how velocity impacts the following behavior. The proposed model is obtained by calculating the field force in the LPF, and its parameters are calibrated using the genetic algorithm. Comparative simulations are executed to verify the remarkable performance of the proposed model, in terms of acceleration, velocity, and headway tracking as well as responding to the cut-in behavior under three different driving conditions.

Assessment on the Acoustic Comfort Inside the Heavy Vehicle Cabin

Abstract Noise, vibration, and harshness (NVH) researchers spend inexhaustible resources of materials, time and money in determining the objective factors that are important in ensuring acoustic comfort in vehicles. In this paper, the factors that directly influence the interior acoustic pressure level in a heavy-duty vehicle were investigated. It was determined using specific descriptors and different units of measurement in assessment of sound levels and the impact generated by noise, the level of interior acoustic pressure and particular values of some prominent sources of noise in the operation of vehicles (engine, HVAC system), taking into account the factors of insurance and thermal comfort, with the aim of determining the cumulative impact at the board of heavy vehicles due to noise.

The Application of Rayleigh Wave Method in the Underground Void Area Exploration

Underground voiding refers to the phenomenon that abnormal looseness, plate breakage, increase in porosity of underground medium lead to the formation of voids that decrease the stability of stratum and weaken the physical and mechanical properties. For example, road underground voiding will seriously affect the comfort and safety of vehicle driving. At present, the engineering geophysical prospecting technology is mainly used to detect the void area. In this paper, the elastic wave simulation method is used to study the response of the Rayleigh wave method to the underground void of the pavement. The response regularity is explored by adjusting the model parameters. The outdoor experiment is carried out according to the law parameters, and the effectiveness of the elastic wave for the detection of shallow surface voids is verified.

A Dynamic Path-Planning Method for Obstacle Avoidance Based on the Driving Safety Field.

Establishing an accurate and computationally efficient model for driving risk assessment, considering the influence of vehicle motion state and kinematic characteristics on path planning, is crucial for generating safe, comfortable, and easily trackable obstacle avoidance paths. To address this topic, this paper proposes a novel dual-layered dynamic path-planning method for obstacle avoidance based on the driving safety field (DSF). The contributions of the proposed approach lie in its ability to address the challenges of accurately modeling driving risk, efficient path smoothing and adaptability to vehicle kinematic characteristics, and providing collision-free, curvature-continuous, and adaptable obstacle avoidance paths. In the upper layer, a comprehensive driving safety field is constructed, composed of a potential field generated by static obstacles, a kinetic field generated by dynamic obstacles, a potential field generated by lane boundaries, and a driving field generated by the target position. By analyzing the virtual field forces exerted on the ego vehicle within the comprehensive driving safety field, the resultant force direction is utilized as guidance for the vehicle's forward motion. This generates an initial obstacle avoidance path that satisfies the vehicle's kinematic and dynamic constraints. In the lower layer, the problem of path smoothing is transformed into a standard quadratic programming (QP) form. By optimizing discrete waypoints and fitting polynomial curves, a curvature-continuous and smooth path is obtained. Simulation results demonstrate that our proposed path-planning algorithm outperforms the method based on the improved artificial potential field (APF). It not only generates collision-free and curvature-continuous paths but also significantly reduces parameters such as path curvature (reduced by 62.29% to 87.32%), curvature variation rate, and heading angle (reduced by 34.11% to 72.06%). Furthermore, our algorithm dynamically adjusts the starting position of the obstacle avoidance maneuver based on the vehicle's motion state. As the relative velocity between the ego vehicle and the obstacle vehicle increases, the starting position of the obstacle avoidance path is adjusted accordingly, enabling the proactive avoidance of stationary or moving single and multiple obstacles. The proposed method satisfies the requirements of obstacle avoidance safety, comfort, and stability for intelligent vehicles in complex environments.

Speed regulation of electric vehicle motor based on PID control

Electric vehicles, as a new technological advancement in the automotive industry for addressing energy and environmental issues, have become a hot topic in both domestic and international car development. The electric vehicle generator, which plays a crucial role, is a key component of electric vehicles. The Alternating Current (AC) motor in electric vehicles is highly efficient and widely used in various fields. Therefore, studying AC motors holds significant theoretical and practical significance. This article first explains the car model and the principle of the electric motor, followed by an analysis of the ProportionalIntegralDerivative (PID) principle. Finally, through PID control, the simulation of the electric vehicle's speed is conducted to achieve better stability and economy. The experiments demonstrate that by improving the phase margin and stability of the lag compensator and feedback loop system, the driving comfort and practicality of electric vehicles can be effectively enhanced.

Analysis of Musculoskeletal Biomechanics of Lower Limbs of Drivers in Pedal-Operation States

In this study, to establish the biomechanical characteristics of commercial vehicle drivers’ muscles and bones while operating the three pedals, a driver pedal-operation simulator was built, and the real-life situation was reconstructed in OpenSim 3.3 software. We set up three seat heights to investigate the drivers’ lower limbs, and the research proceeded in two parts: experiment and simulation. Chinese adult males in the 95th percentile were selected as the research participants. In the experiment, Delsys wireless surface electromyography (EMG) sensors were used to collect the EMG signals of the four main muscle groups of the lower limbs when the drivers operated the three pedals. Then, we analyzed the muscle activation and the degree of muscle fatigue. The simulation was based on OpenSim software to analyze the driver’s lower limb joint angles and joint torque. The results show that the activation of the hamstrings, gastrocnemius, and rectus femoris muscles were higher in the four muscle groups. In respect of torque, in most cases, hip joint torque > knee joint torque > ankle joint torque. The knee joint angles were the largest, and the ankle joint angles changed the most. The experimental results provide a reference for improving drivers’ handling comfort in commercial vehicles and provide theoretical bases for cab design and layout optimization.

An overview of the development of intelligent materials and active vibration isolation systems for vehicles

Intend to reduce the impact of external vibrations on the smoothness of automotive precision instruments and vehicles and to improve the operational accuracy of automotive precision instruments and the comfort of passenger vehicles, vibration isolation technologies are used and active control systems are applied to vibration isolation systems. The extensive use of smart materials in vibration isolation systems has enabled the design of vehicle structures based on smart materials to meet the suppression of vehicle vibrations well. This paper reviews the application of commonly used smart materials to the field of vehicle vibration damping, summarizes the configuration design of single-axis and multi-axis vibration isolation systems, and develops the thinking behind the application of active control technology to other carriers, pointing out the future research direction of current smart materials for vehicles.

Bi‐objective Trade‐Off Optimization Control Strategy Based on the Equivalent Consumption Minimization Strategy–Pareto Algorithm for a Multimode Hybrid Electric Vehicle

Considering the trade‐off on the improvement of fuel economy performance and mode transition comfort for multimode hybrid electric vehicles (MMHEV), a bi‐objective trade‐off control strategy is designed based on the equivalent consumption minimization strategy (ECMS) with Pareto method. Aiming at the problem of optimal economy of multimode working area of vehicles, the equivalent fuel consumption cost and torque distribution MAP in different modes are determined based on ECMS. In order to solve the problem of torque instability caused by engine response lag and demand torque fluctuation, the motor torque optimization coefficient (MTOC) is introduced as the control variable by taking advantage of the motor's fast and accurate response to torque, and the genetic algorithm is used to optimize the MTOC, and a smoother torque distribution is obtained. Because there is a coupling relationship between the economy and ride comfort of the system, the trade‐off optimization is carried out using the NSGA‐II algorithm based on Pareto principle. The simulation verification conducted in nonslope and slope conditions, as well as hardware‐in‐the‐loop experiments, demonstrates the effectiveness of the proposed control strategy in managing the trade‐off between economy and ride comfort for the MMHEV.

Probability distributions for stochastic comfort in railway vehicles

Comfort has traditionally been assessed as a single deterministic index that can be assigned to each railway vehicle type (at a given speed on a given track quality level). However, it is now well established that passengers influence vibration and, as a consequence, occupancy level and seating arrangement influence comfort, thus turning it into a stochastic variable. The concept of Compound Comfort, presented in Palomares et al. [Is the standard ride comfort index an actual estimation of railway passenger comfort? Veh Syst Dyn. 2022;1–14. doi: 10.1080/00423114.2022.2148543], is used in this paper to evaluate several train types. Simplified models are used as a first approximation for vibration analysis. Despite model simplicity, since the number of possible seating arrangements is intractable, a Monte Carlo procedure is used to obtain compound comfort probability density distributions from a randomised subset of cases. The results from the work presented here will show that the information provided by stochastic distributions is much richer than a single deterministic index. Nevertheless, obtaining distributions from Monte Carlo tests (numerical or experimental) is impractical for any commercial assessment of comfort. Therefore, an inference procedure is called for and has been devised in order to obtain probability density function parameters from just one tare test, along with ten runs of a half laden test. This recipe has been adapted from one presented previously to be able to accommodate the skewed distributions that emerge when a wide range of train configurations is considered.

Evaluation of Ride Comfort under Vortex-Induced Vibration of Long-Span Bridge

The increasing number of suspension bridges has led to designs favoring greater length and flexibility, resulting in a common problem of vortex-induced vibration. While vortex-induced vibration typically does not cause structural damage, it diminishes the bridge’s fatigue resistance and has a detrimental impact on ride comfort. Additionally, this study introduces a road–bridge–vehicle vibration model, proposing an evaluation method for assessing ride comfort during vortex-induced vibrations in long-span bridges. This method features simplified modeling and swift calculations, circumventing the need for intricate finite element modeling and iterative solving. Furthermore, it evaluates ride comfort for vehicles crossing a prototype long-span suspension bridge using the Overall Vibration Total Value (OVTV) and Motion Sickness Incidence (MSI) criteria. This study also analyzes the influence of various parameters on OVTV and MSI, including vehicle speed, road grade, vortex-induced vibration frequency, and amplitude. It establishes a reference limit for vortex-induced vibration amplitude based on OVTV and MSI values. Moreover, the study substantiates that, within the context of vortex-induced vibration, the MSI value is more suitable for evaluating driving comfort compared to the OVTV.

A Review on Various Control Strategies and Algorithms in Vehicle Suspension Systems

Automotive suspension systems provide passenger safety, ride comfort and vehicle handling in passenger and commercial vehicles. Through extensive research in the last couple of decades coupled with the recent advancements in technology, the improvement in vehicle handling and ride comfort have been significant by using various control strategies in semi-active and fully active suspension systems. Despite a significant number of articles available on the enhancement and improvement of vehicle suspension systems, there is certainly a lack of knowledge on various control strategies and algorithmic techniques used in the vehicle suspension system. Thereby, to address the gap, this review consecutively attempts to comprehensively explore the various research work conducted on the various control strategies used in vehicle suspension systems.

Effect of heat mitigation strategies on the thermal environment of hardened pavement and pedestrian thermal comfort in a hot and humid area: A case study of Guangzhou, China.

The synergistic effect of heat waves and urban heat islands (UHI) adversely affect the urban environment, building energy consumption, and human health. The absorption and storage of short-wave radiation by hardened pavement is the primary reason for high-temperature heat waves and the UHI effect. Three mitigation strategies were assessed to alleviate the influence of high-temperature hardened pavement on the thermal environment and thermal comfort of pedestrians, water-spray vehicles (spray) and pavement watering (watering) to take advantage of evaporative cooling, and a fan based on convective heat transfer. In addition, the fan-spray and fan-watering combinations were evaluated to increase the evaporative cooling rate. Field measurements showed that the five heat mitigation strategies improved the thermal environment and reduced environmental thermal stress. The thermal sensation, comfort sensation, and mean skin temperature (MST) were analyzed in thermal perception experiments. The result indicated that the mitigation strategies changed the subjects' thermal perception. Moreover, regression analysis between the universal thermal climate index (UTCI) and the thermal response showed that the neutral temperature and the range of comfort threshold of UTCI and MST increased after implementing the mitigation strategies.

A nonlinear biodynamic model of seated human body exposed to vertical vibration with sensitivity analysis

The nonlinearity observed in the apparent mass of a seated human body exposed to vertical vibration demonstrates a decrease in resonance frequency as the vibration magnitude increases. However, there is a dearth of appropriate models that accurately capture this nonlinear biodynamic response. Furthermore, the impact of different properties of human body parts on this nonlinearity remains unexplored. This paper presents a model that effectively characterizes the nonlinearity in the apparent mass of a seated human body subjected to vertical vibration.The proposed model incorporates the legs, thighs, pelvis, torso, head, and viscera as key components. Nonlinear springs are employed to simulate the dynamic interactions between the human body and the seat, as well as the connection between the viscera and the pelvis/torso. To validate the model, vertical in-line and fore-and-aft cross-axis apparent masses were measured at the seat pan for 11 subjects without backrest contact, using three different vibration magnitudes (0.4, 0.6, and 1.0 m/s2 r.m.s.).A comprehensive global sensitivity analysis was conducted with the calibrated model to identify the factors that have the greatest influence on the biodynamic response. The results revealed that the stiffness of the soft tissues beneath the thighs, the mass of the thighs, and the mass of the torso were the three most influential parameters affecting the apparent mass. When considering the degree of nonlinearity in the apparent mass, the stiffness of the soft tissues beneath the thighs and the mass of the torso contributed the most.The proposed model holds significant potential for studying the nonlinear biodynamic responses of vehicle drivers and passengers. It provides a valuable tool for gaining insights into the intricate dynamics of human body vibration and can contribute to the development of improved seating systems and enhanced ride comfort in vehicles.

Active Suspension Robust Preview Control by Considering Actuator Delay

Active suspension systems (ASSs) are crucial for realizing the improvement demand of ride comfort in autonomous vehicles (AVs). This paper presents a novel integrated robust preview control (PC) algorithm to further improve the ride comfort by effectively handling actuator delay. An augmented ASS model is first established to consider actuator delay. Then, to obtain the time-domain feedforward disturbance, updating the local spatial road dataset from sensing systems by low-pass filtering and introducing speed for conversion. A predictive control framework that utilizes preview road disturbances is developed to achieve better ride comfort. And assuming parameterized disturbances, it is transformed into a consistent quadratic programming (QP) problem for real-time application in ASS. Furthermore, an innovative design of combined observer provides accurate and robust observations under multiple uncertainties, with which the algorithm can effectively compensate for actuator delay under different road conditions. Finally, the bounded-input bounded-output (BIBO) stability of the algorithm is well demonstrated. Simulation and bench test results indicate that the proposed algorithm can not only significantly improve road holding and ride comfort, but also realize a robust observation of the augmented ASS state. In addition, the solving time of the bench test satisfies the real-time requirements of the algorithm.

Modelling and Dynamic Analysis of Adaptive Neuro-Fuzzy Inference System-Based Intelligent Control Suspension System for Passenger Rail Vehicles Using Magnetorheological Damper for Improving Ride Index

The ride comfort and safety of passenger rail vehicles depend on the performance of the suspension system in attenuating vibrations induced by track irregularities. This paper investigates the effectiveness of an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based semi-active controlled suspension system using a magnetorheological fluid damper in reducing nonlinear lateral vibrations of a passenger rail vehicle. A complete rail vehicle model is developed, including the carbody, front and rear bogies, and the passive suspension system’s nonlinear stiffness and damping characteristics are considered from experimental data. The passive suspension model is validated through experiments, and an ANFIS-based controller is incorporated with the secondary vertical suspension system to improve ride behavior. Three semi-active suspension strategies are considered under varying speeds and track irregularities, and their effectiveness is compared to the nonlinear passive suspension system in terms of rms acceleration, rms displacement, ride quality, and comfort. The results shows that the ANFIS-based semi-active suspension system with a magnetorheological fluid damper outperforms the passive suspension system and semi-active strategies in all tested conditions. There is a reduction in rms acceleration by approximately 11.11% to 23.64% and rms displacement by about 5.36% to 32.06%. Moreover, it significantly improves ride quality (9.20% to 31.02%) and comfort (9.96% to 31.50%). The rms acceleration and displacement are reduced, and the Sperling ride index and Percentage Reduction Index values demonstrate that the ANFIS-based semi-active suspension effectively minimizes the impact of rail irregularities and vibrations, resulting in a significant gain in ride quality and passenger comfort.