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A road test on semi-trailers is carried out, and accelerations of some characteristic points on the braking system,axles,and truck body is measured,also brake pressure and noise around the support frame is acquired.The measured data was analyzed to determine the causes of the brake noise, and the mechanism of the noise of the drum brake of semi-trailers during low-speed braking was investigated. The following conclusions are obtained: (1) Brake noise of the drum brake of the semi-trailer at low-frequency is generated from vibrations of the brake shoes, axle, and body, and the vibration frequency is close to 2nd natural frequency of the axle. (2) Brake noise is generated from stick-slip motion between the brake shoes and the brake drum, where the relative motion between the brake drum and the brake shoes is changed alternately with sliding and sticking, resulting in sudden changes in acceleration and shock vibration.

An experiment is carried out to measure creep groan of a drum brake located in a trailer axle of a truck. The noise nearby the drum brake and accelerations on brake shoes, axle and trailer frame are collected to analyze the occurring conditions and characteristics of the creep groan. A multi-body dynamics model with 1/4 trailer chassis structures is established for analyzing brake component vibrations that generates the creep groan. In the model, the contact force between brake cam and brake shoes, the contact friction characteristics between brake linings and inner circular surface of brake drum, and the properties of chassis structure are included. Dynamic responses of brake shoes, axle and trailer frame during the braking process are estimated using the established model and the responses are compared with the measured results, which validate the model.

In order to study the effects of different factors on the static and dynamic characteristics of air springs, three models were established to calculate the static and dynamic characteristics of air springs, including modeling at the design position, modeling only considering the straight state, and modeling considering the thickness of the bellows in the straight state. Static stiffness of air springs is calculated using three different models and are compared with experiments. In the straight state model considering the thickness of the bellow, the influence of aluminum tube and bellows thickness on the static stiffness are considered, and the modeling with the straight state solved the problem of the change in cord angle after the air spring was inflated and expanded. The established model is then used to calculate static and dynamic characteristics of air springs, such as static stiffness, hysteresis loop, and dynamic stiffness.

The fatigue prediction model of an air spring based on the crack initiation method is established in this study. Taking a rolling lobe air spring with an aluminum casing as the studying example, a finite element model for analyzing force versus displacement is developed. The static stiffness and dimensional parameters of limit positions are calculated and analyzed. The influence of different modeling methods of air springs bellow are compared and analyzed. Static stiffness measurement of an air spring is conducted, and the calculation results and the measured results of the static stiffness are compared. It is shown that the relative error of the measured stiffness and calculated stiffness is within 1%. The Abaqus post-processing stage is redeveloped in Python language.

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this paper, a human-centric approach is adopted to provide an enriching driving experience. We perform data analysis of the naturalistic behavior of drivers when performing lane change maneuvers by extracting features from extensive Second Strategic Highway Research Program (SHRP2) data of over 5,400,000 data files.

In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module.

This paper presents an adaptive H2/H∞ control strategy for a semi-active suspension system with unknown suspension parameters. The proposed strategy takes into account the damping force characteristics of continuous damping control (CDC) damper. Initially, the external characteristics of CDC damper were measured, and a forward model and a back propagation (BP) neural network inverse model of CDC damper were proposed using the measured data. Subsequently, a seven-degree-of-freedom vehicle with semi-active suspension system and H2/H∞ controller was designed. Multiple feedback control matrices corresponding to different sprung mass parameter values were determined by analyzing time and frequency domain performance. Finally, a dual observer system combining suspension state and parameter estimation based on the Kalman filter algorithm was established.

Tortuosity, viscous characteristic length and thermal characteristic length are three important parameters for estimating the acoustic performance of porous materials, and it is usually measured by ultrasonic measurement technology, which is costly. In this paper, a method for identifying the tortuosity, viscous characteristic length and thermal characteristic length for the porous fiber materials mixed with kapok fiber and two kinds of other fiber materials is proposed. The tortuosity is calculated by using the porosity and high-frequency normal sound absorption coefficient of porous materials. According to the normal sound absorption coefficient curve of porous materials under plane wave incidence, viscous characteristic length and thermal characteristic length are identified through the Johnson-Champoux-Allard-Lafarge (JCAL) model and genetic algorithm by using the measured parameters, the calculated tortuosity and static thermal permeability.

To reduce the noise in the frequency range of 100Hz~1000Hz, a metamaterial structure composed of lightweight frame, hard membrane-like material and added mass is proposed in this paper. The advantage of this structure is that it is lightweight and the membrane-like material does not need to be stressed in advance. Finite element method (FEM) and experiment are used to investigate the sound transmission loss (STL) performance of the metamaterial structure. The results show that the peak STL is caused by the local resonance of the added mass and the membrane-like material. The valley versus frequency results from the resonance frequencies of metamaterial structure, and it is divided into three resonance frequencies: resonance frequencies from added mass, membrane-like material and frame.

Suspension systems are an integral part of land vehicles and contribute significantly to the vehicle performance in terms of its ride comfort and road holding characteristics. In the case of Space Exploration Vehicles (SEVs), the requirement of these unmanned vehicles is to rove, collect pictures and transmit data back to the earth. This is generally performed with the help of exteroceptive, and proprioceptive sensors mounted on the main chassis of the SEV. The design of various components of such vehicles is dictated by the assumption of extreme terrain and environmental conditions that it might face. The Mars Exploration Rovers (MERs) have incorporated the use of the “Rocker-Bogie” mechanism for the suspension system which provides relative stability to the MER for various maneuvers. In this work, the “Rocker-Bogie” mechanism is modeled and simulated as a planar kinematic model using parameters of the Perseverance rover.

Layered materials are one of the most commonly used acoustical treatments in the automotive industry, and have gained increased attention, especially owing to the popularity of electric vehicles. Here, a method to model and couple layered systems with various layer types (i.e., poro-elastic layers, solid-elastic layers, stiff panels, and fluid layers) is derived that makes it possible to stably predict their acoustical properties. In contrast with most existing methods, in which an equation system is constructed for the whole structure, the present method involves only the topmost layer and its boundary conditions at two interfaces at a time, which are further simplified into an equivalent interface. As a result, for a multi-layered system, the proposed method splits a complicated system into several smaller systems and so becomes computationally less expensive.

Rapid adoption of battery electric vehicles means improving the energy consumption and energy efficiency of these new vehicles is a top priority. One method of accomplishing this is regenerative braking, which converts kinetic energy to electrical energy stored in the battery pack while the vehicle is decelerating. Coasting is an alternative strategy that minimizes energy consumption by decelerating the vehicle using only road load. A battery electric vehicle model is refined to assess regenerative braking, coasting, and other deceleration strategies. A road load model based on public test data calculates tractive effort requirements based on speed and acceleration. Bidirectional Willans lines are the basis of a powertrain model simulating battery energy consumption. Vehicle tractive and powertrain power are modeled backward from prescribed linear velocity curves, and the coasting trajectory is forward modeled given zero tractive power.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

This paper provides a simulation analysis of a novel interconnected roll stability control (RSC) system for improving the roll stability of semitrucks with double trailers. Different from conventional RSC systems where each trailer’s RSC module operates independently, the studied interconnected RSC system allows the two trailers’ RSC systems to communicate with each other. As such, if one trailer’s RSC activates, the other one is also activated to assist in further scrubbing speed or intervening sooner. Simulations are performed using a multi-body vehicle dynamics model that is developed in TruckSim® and coupled with the RSC model established in Simulink®. The dynamic model is validated using track test data. The simulation results for a ramp steer maneuver (RSM) and sine-with-dwell (SWD) maneuver indicate that the proposed RSC system reduces lateral acceleration and rollover index for both trailers, decreasing the likelihood of wheel tip-up and vehicle rollover.

If a car is braked frequently or at high speed, the thermal decay of brake system performance appears, which reduces the braking performance of the car. To compensate brake moment reduction during braking at thermal decay of brake system, a compensation strategy of brake moment is designed by using “feedforward +PID feedback” to pressure at wheel braking cylinder. The trigger and exit conditions of the strategy for the wheel cylinder pressure are proposed based on the threshold. A vehicle model consisting braking system is established if a vehicle runs at straight line, and the braking distance and braking acceleration are estimated, the results shown that the thermal decay compensation control strategy proposed in this paper can reduce the braking distance and braking time.

Taking a closed airbag suspension system as studying objects, the nonlinear dynamic model of the reservoir, compressor, solenoid valve, pipeline and air spring is established. The compressor exhaust volume, solenoid valve flow rate and air spring charging and discharging rate are calculated and compared with experiment to validate the model. Taking pressure difference and height adjustment rate under different working conditions of an airbag suspension as control measures, a control strategy is developed based on the established nonlinear dynamic model. The result indicates that when the vehicle is in curb weight, design weight and GVW (gross vehicle weight), the working time of the compressor can be reduced by 13.6%, 15.1% and 46.5%, respectively, compared with the conventional mode, during a height adjustment cycle. Then a state observer is proposed to estimate the steady-height for reducing the disturbance of measured height from road excitation.

Air springs with auxiliary chambers (ASAC) are widely used in automotive suspension systems. The introducing of the auxiliary chamber and the connecting flow passage makes the system more complex, especially in which case an additional resonance peak caused by the air inertia in a connecting pipe appears. To characterize the nonlinear dynamic characteristics, this paper proposes a novel physical-neural network hybrid modeling method for ASACs. Firstly, experiments are carried out to measure the dynamic characteristics of ASACs. Then, based on the thermodynamic principle, a nonlinear dynamic characteristic model for the ASAC is developed and a linearized process is performed to obtain a linearized physical model. Due to the amplitude dependence and frequency dependence in the dynamic characteristics of ASACs, the physical model cannot accurately characterize these nonlinearities.

Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme.

The identification of vehicle noise is the basis for studying the acoustic characteristics of vehicles. In this paper, both excitation of noise sources and response of interior noise were identified. Firstly, a transfer path analysis (TPA) model was established to identify the excitation of noise sources, which includes vehicle main noise sources, such as engine, tire, exhaust pipe and muffler. Based on the operational signals and transfer function which were tested in the vehicle semi-anechoic room, the excitation of noise sources was identified using inverse matrix method. Identify result indicated that tires have higher excitation amplitude than engine in high frequency band. Therefore, the transfer path between the tire and the cabin, such as carpet and windshield, should be taken as the focus of acoustic performance improvement. By improving the acoustic material on the transfer path, the loss of sound in the transfer path will be increase.

The pre-prototype development of a simulated rule-based hybrid energy management strategy for a 2019 Chevrolet Blazer RS converted parallel P4 full hybrid is presented. A vehicle simulation model is developed using component bench data and validated using EPA-reported dynamometer fuel economy test data. A combined Willans line model is proposed for the engine and transmission, with hybrid control rules based on efficiency-derived engine power thresholds. Algorithms are proposed for battery state of charge (SOC) management including engine loading and one pedal strategies, with battery SOC maintained within 20% to 80% safe limits and charge balanced behavior achieved. The simulated rule-based hybrid control strategy for the hybrid vehicle has an energy consumption reduction of 20% for the Hot 505, 3.6% for the HwFET, and 12% for the US06 compared to the stock vehicle.