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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.

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.

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.

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 vehicle will produce certain shock and vibration during the braking process, which will affect the driving experience of the driver. Aiming at the problems of pitch vibration, longitudinal vibration and shock during the braking process, this paper proposes a planning and following control method for target longitudinal acceleration in post-braking phase, and designs control trigger strategies. Target longitudinal acceleration planning takes minimizing longitudinal shock as the design goal. The following control takes the brake pressure as the control object, and adopts the “feedforward +PID feedback” method to follow the target longitudinal acceleration. Besides, considering the safety of braking process, the trigger condition of control is designed which utilizes BP neural network method to judge whether the control has to be triggered. Based on Simulink software, the simulation model of straight-line braking is established.

The thermal management system, which is used to improve driving safety and thermal comfort, is one of the most important systems in electric vehicles. In recent years, researchers have coupled the heat pump system and the battery cooling system to effectively improve the heating COP (Coefficient of Performance). Therefore an accurate dynamic model of thermal management system plays a key role in investigating system performance and optimal control strategies. In this paper, an electric vehicle thermal management system based on four-way valve heat pump system is designed. The moving boundary method is improved by considering the unsteady flow of the external fluid, and then a 13-order dynamic model of the thermal management system is established. Firstly, the control equations of evaporator, condenser and chiller are derived according to the principle of conservation, and then a dynamic model of thermal management system is established in Simulink.

Uniaxial fatigue tests of rubber dumbbell specimens under different mean and amplitude of strain are carried out. An Extreme Learning Machine (ELM) model optimized by Dragonfly Algorithm (DA) is proposed to predict the fatigue life of rubber based on measured rubber fatigue life data. Mean and amplitude of strain and measured rubber fatigue life are taken as input variables and output variables respectively in DA-ELM model. For comparison, genetic algorithm (GA) and particle swarm optimization (PSO) are used to optimize ELM parameters, and GA-ELM and PSO-ELM models are established. The comparison results show that DA-ELM model performs better in predicting the fatigue life of rubber with least dispersion. The coefficients of determination for the training set and test set are 99.47% and 99.12%, respectively. In addition, a life prediction model equivalent strain amplitude as damage parameter is introduced to further highlight the superiority of DA-ELM model.

In order to enhance the efficiency of durability testing of automobile parts, a time-frequency domain accelerated editing method of road load time series of rubber mount on powertrain was discussed. Based on Stockwell Transform method and Accumulative Power Spectral Density, a new time-frequency domain accelerated editing method (ST-APSD) was proposed. The accumulative power spectral density was obtained by ST of the load time series signal of automobile powertrain rubber mounting force which is acquired by the real vehicle in the test field. Based on the accumulative power spectral density, the threshold value was proposed to identify and delete the small damage load fragments, and then the acceleration spectrum was obtained.

The durability road test of a vehicle is an important test to verify the reliability of vehicle components. In order to carry out the durability bench test for drive shaft systems of all-terrain vehicles, a method for acquiring time domain signals of articulation angles of the CVJ, input torque, and rotational speeds of drive shaft systems is proposed. The acquired load spectrum of drive shaft systems is preprocessed including deleting small amplitudes, de-drifting, deburring, filtering, etc. Peaks and valleys are extracted from the preprocessed load spectrum. Based on the graphic method and the estimator stabilization method, the upper and lower thresholds of the time domain extrapolation of the load spectrum are determined, and then the peaks and valleys excesses that exceed the upper and lower thresholds are extracted. The generalized pareto distribution function is used to fit the distribution of peaks and valleys excesses.

The tensioner of the engine front end accessory drive system was taken as a study object, and the mechanical structure and working principle of the automatic tensioner were analyzed. The hysteresis behavior test of tensioner torque-angular displacement was carried out, and the effects of different excitation frequencies and excitation amplitudes on the hysteresis behavior of the tensioner were analyzed. According to the modified Dahl hysteresis model, the model parameters of the tensioner was identified. Based on the identified model parameters, the hysteresis behavior of the tensioner was calculated, and the calculation model accuracy was verified with the tested results. The influence of the hysteresis curve transition area exponent on the tensioner behavior was studied. The dynamic behavior of the engine front end accessory drive system was simulated using the simulation software.

As one of the key components of the heat pump system, the electronic expansion valve mainly plays the role of throttling and reducing pressure in the heat pump system. The refrigerant flowing through the orifice will produce complex phase change. It is of great significance to study the internal flow field by means of CFD calculations. Firstly, a three-dimensional fluid model is established and the mesh is divided. Secondly, the phase change model is selected, the material is defined and the boundary conditions are determined. According to the principle of the fluid passing through thin-walled small holes, the flow characteristics of electronic expansion valve are theoretically analyzed. Then the flow characteristics of expansion valve are numerically calculated, and a bench for testing mass flow rate of the expansion valve is built. Then the theoretical value, CFD value and experimental value are compared to verify the correctness of the established three-dimensional fluid model.

To solve the contradiction between model complexity and the warning accuracy of the algorithm of the vehicle rollover warning, a rollover state warning method based on the secondary predictive zero-moment point position for vehicles is proposed herein. Taking a sport utility vehicle(SUV) as the research object, a linear three-degrees-of-freedom vehicle rollover dynamics model is established. On the basis of the model, the lateral position of the zero-moment point and its primary and secondary rates of change are calculated. Then, the theoretical solution of time-to-rollover of the vehicles is deduced from the lateral position of the secondary predictive zero-moment point. When the rollover warning index, the lateral position of the zero-moment point, is greater than the set threshold, the active anti-rollover control system will be triggered. The active anti-rollover braking control system adopts a hierarchical control strategy.