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With the increase of motor speed and the deterioration of operating environment, it is more difficult to predict the transient temperature field (TTF). Meanwhile, it is difficult to obtain the temperature test dataset of key nodes under various complete road conditions, so the cost of bench test or real vehicle test is high. Therefore, it is of great significance to establish a high fidelity, lightweight temperature prediction model which can be applied to real vehicle thermal management for ensuring the safe and stable operation of motor. In this paper, a physical model simulating electromagnetic-heat-flow multi-physical coupling of permanent magnet synchronous motor (PMSM) in electric drive gearbox (EDG) is established, and the correctness of the model is verified by the actual EDG bench test.

The acoustic muffler is one of the practical solutions to reduce the noise in ducts. The acoustic and aerodynamic performances are two critical indices of one muffler for the air intake system of a hydrogen fuel cell electric vehicle (FCEV). In this study, the concept of phononic crystal is applied to design the muffler to obtain superior acoustic performance. One duct with periodic and compact resonator-type mufflers is designed for broadband noise attenuation. The two-dimensional (2D) transfer matrix method and bandgap theory are employed to calculate the transmission loss (TL) and acoustic bandgap. It is numerically and theoretically demonstrated that broadband noise attenuation could be acquired from 500Hz to 3500Hz. Afterwards, the three-dimensional (3D) computational fluid dynamics (CFD) approach is applied to predict the pressure distribution. The results indicate that the proposed hybrid muffler and the phononic crystal duct possess low pressure loss values.

Most centrifugal pendulum vibration absorber (CPVA) research focuses on the horizontal or vertical plane, ignoring the influence of gravity. However, with the wide application of CPVAs in the automobile industry, some gravity-related problems have been encountered in practice. In this study, employing the second kind of Lagrange equation, the differential equation of motion of a CPVA is established, and the first-order approximate analytical solution is solved using the method of multiple scales. The mathematical relations among the excitation torque amplitude and phase, gravity influence, absorber trajectory shape, absorber position, viscous damping coefficient, and mistuning level parameters are provided for study. Specifically, the second-order responses of four absorbers and two absorbers in a gravity field are studied, and the influence of the change in the torque excitation phase on the response of the absorber is thoroughly analyzed.

The displacement of the shaft head fails to be accurately measured while the three-axle heavy-duty truck is driving on the reinforced pavement. In order to obtain accurate fatigue load spectrum of the suspension bracket, the acceleration signals of the shaft heads of the suspension obtained by the reinforced pavement test measurement are virtually iterated as responses. A more accurate model of the rigid-flexible coupled multi-body dynamics (MBD) of the whole vehicle is established by introducing a flexible frame based on the comprehensive modal theory. Furthermore, the vertical displacements of the shaft heads are obtained by the reverse solution of the virtual iterative method with well-pleasing precision. The accuracy of the virtual iteration is verified by comparing the simulation results with the vertical acceleration of the shaft head under the reinforced pavement in the time domain and damage domain.

The driver monitoring system (DMS) plays an essential role in reducing traffic accidents caused by human errors due to driver distraction and fatigue. The vision-based DMS has been the most widely used because of its advantages of non-contact and high recognition accuracy. However, the traditional RGB camera-based DMS has poor recognition accuracy under complex lighting conditions, while the IR-based DMS has a high cost. In order to improve the recognition accuracy of conventional RGB camera-based DMS under complicated illumination conditions, this paper proposes a lightweight low-illumination image enhancement network inspired by the Retinex theory. The lightweight aspect of the network structure is realized by introducing a pixel-wise adjustment function. In addition, the optimization bottleneck problem is solved by introducing the shortcut mechanism.

Alternating current (AC) heating is an efficient and homogeneous manner to warm Lithium-ion batteries (LIBs) up. The integrated design of AC heating combined with the motor drive circuit has been studied by many scholars. However, the problems of excessive heating frequency (>1kHz) and zeros torque output of the motor during the heating process have not been solved. High-frequency AC excitation may be detrimental to the battery because the effect of high-frequency AC excitation on the state of health of the battery is unknown. In addition, although the zero-torque output can be realized by controlling the q-axis current to zero, the torque ripple is still difficult to eliminate in a real-world application. To further solve the above problems, the motor’s neutral conductor is pulled out and connected to a large capacitor to increase the current amplitude of the AC heating at low frequencies.

To improve the maneuverability and energy consumption of an electrical vehicle, a two-level speed control method based on model predictive control (MPC) is proposed for accurate control of the vehicle during downhill coasting. The targeted acceleration is planned using the anti-interference speed filter and MPC algorithm in the upper-level controller and executed using the integrated algorithm with the inverse vehicle dynamics and proportional-integral-derivative control model (PID) in the lower-level controller, improving the algorithm’s anti-interference performance and road adaptability. Simulations and vehicle road tests showed that the proposed method could realize accurate real-time speed control of the vehicle during downhill coasting. It can also achieve a smaller derivation between the actual and targeted speeds, as well as more stable speeds when the road resistance changes abruptly, compared with the conventional PID method.

Aiming at the laborious process in motor structure modeling for acoustic noise calculation, an improved stator structure modeling scheme is proposed, which includes stator structure simplification and equivalent material parameters identification. The stator assembly is modeled as a homogeneous solid with the same size as the stator core, and the influence of model simplification is compensated by orthotropic equivalent material parameters. The equivalent material parameters are acquired through an optimization algorithm by minimizing the error between FEM calculated modal frequencies and the modal tested results. With the stator assembly model, the motor assembly model is built, and the constrained modal characteristics of the motor assembly are verified by comparing the modal frequencies to the resonance bands in the vibration acceleration spectrum. Finally, the motor structure model is used to calculate the electromagnetic noise of an induction motor.

With the growing prosperity of the long-distance freight and urban logistics industry, the demand for cargo trucks is gradually increasing. The connecting bracket is the critical connecting part of the truck chassis, which bears the load transmitted by the road excitation and reduces the damage to the frame caused by the load. However, the occurrence of rough road conditions is inevitable in heavy-duty transportation. In this paper, road durability tests and fatigue life analysis are carried out on the original structure to ensure the safety of the vehicle. Based on the known boundary and load constraints, a lightweight and high-performance structure is obtained through size optimization, as the original structure cannot meet the performance requirements. Firstly, the road test was conducted on the truck where the original bracket structure is located.

Harmony-with-traffic refers to the ability of autonomous vehicles to maximize the driving benefits such as comfort, efficiency, and energy consumption of themselves and the surrounding traffic during interactive driving under traffic rules. In the test of harmony-with-traffic, one or more background vehicles that can respond to the driving behavior of the vehicle under test are required. For this purpose, the functional requirements of car-following model for harmony-with-traffic evaluation are analyzed from the dimensions of test conditions, constraints, steady state and dynamic response. Based on them, an interactive car-following model (ICFM) is developed. In this model, the concept of equivalent distance is proposed to transfer lateral influence to longitudinal. The calculation methods of expected speed are designed according to the different car-following modes divided by interaction object, reaction distance and equivalent distance.

The intersection is recognized as the most dangerous area because of the restricted road structures and indeterminate traffic regulations. Therefore, according to the Vehicle-to-everything (V2X) communication, Intelligent Transportation Systems (ITS), and Digital Twin data, we present a potential energy field method to establish the general characteristics of intersection traffic safety, evaluate the safety situation of intersection and assist intersection traffic participants in passing through the intersection safer and more efficient. The resulting potential energy field method is established by the contour line of traffic participants' potential energy, which is constructed as a superposition of disparate energies, such as boundary potential energy, body potential energy, and velocity potential energy. The intersection traffic safety is evaluated by the potential energy field characteristic of simultaneous intersection traffic participants.

With the popularity of automated vehicles, the future mixed traffic flow contains automated vehicles with different degrees of intelligence developed by other manufacturers. Therefore, simulating the interaction behavior of automated vehicles with varying levels of intelligence is crucial for testing and evaluating autonomous driving systems. Since the algorithm of traffic vehicles with various intelligence levels is difficult to obtain, it leads to hardships in quantitatively characterizing their interaction behaviors. Therefore, this paper designs a new automated vehicle test platform to solve the problem. The intelligent vehicle testbed with multiple personalized in-vehicle control units in the loop consists of three parts: 1. Multiple controllers in the loop to simulate the behavior of traffic vehicles；2. The central console applies digital twin technology to share the same traffic scenario between the tested vehicle and the traffic vehicle, creating a mixed traffic flow. 3.

In this paper, the principles, advantages and disadvantages of the main technology of variable strength design of automobile B-pillar Based on the finite element simulation technology, the local stress variable strength design effect of Automobile B-pillar structure is simulated, compared and evaluated. The simulation results show that with the same mechanical properties, the overall lightweight degree of B-pillar structure with variable strength design can be reduced by about 8.9%. With the expansion of the strengthening area of variable strength design of parts, the degree of lightweight of parts can be further improved. It can be seen that the local stress variable strength design method provides a new technical option for the lightweight design of automobile parts.

Centrifugal Pendulum Vibration Absorber (CPVA for short) is used to absorb torsional vibrations caused by the shifting motion of the engine. It is increasingly used in modern powertrains. In the research of the dynamic characteristics of the CPVA, it is necessary to obtain the real motion of the pendulum to compensate the fitting performance of mathematical model. The usual method is to install an angle sensor to measure the movement of the pendulum. On the one hand, the installation of the sensor will affect its movement to a certain extent, so that the measurement results do not match the actual motion. On the other hand, the motion of the pendulum is not only the rotational motion around the rotational axis of the CPVA rotor, but also has translation relative to it. As a result, it is difficult to obtain accurate motion only by the angle sensor. We proposed a non-contact centrifugal pendulum motion measurement method.

There are often a large number of design variables and responses in suspension hard point optimization design. The traditional optimization strategy integrating heuristic algorithm and simulation model is not applicable due to its low efficiency. To solve optimization problems with huge number of design variables and responses, a multi-objective optimization framework combined heuristic optimization algorithm with multi-objective decision-making method is developed. Specifically, the multi-objective optimization was performed by dividing the problem into two independent sub-problems of multi-objective optimization and multi-objective decision-making. Further, to reduce the number of sample points required for building a surrogate model, a two-stage multi-objective optimization is proposed.

Subframe is an important part of automobile chassis, which is connected with body, suspension control arm, powertrain mount, etc. The dynamic stiffness value of the connection point is an important performance index of the subframe, which affects the vibration of the vehicle body. This paper introduces the basic concept and related theory of dynamic stiffness, derives the theoretical formula of dynamic stiffness, and analyzes the frequency response of the key points of the subframe. In view of the fact that the dynamic stiffness of the subframe of a certain vehicle model is not up to the standard at some connection points, the dynamic stiffness CAE simulation analysis is carried out to determine the frequency range of insufficient dynamic stiffness and the connection points that need to be optimized.

To overcome the shortcoming that vehicles with multiple steering modes need to switch steering modes at parking or very low speeds, a dynamic switch method of steering modes based on MOEA/D (Multi-objective Evolutionary Algorithm Based on Decomposition) was proposed for 4WID-4WIS (Four Wheel Independent Drive-Four Wheel Independent Steering) electric vehicle, considering the smoothness of dynamic switch, the lateral stability of the vehicle and the energy economy of tires. First of all, the vehicle model of 4WID-4WIS was established, and steering modes were introduced and analyzed. Secondly, the conditions for the dynamic switch of steering modes were designed with the goal of stability and safety. According to different constraints, the control strategy was formulated to obtain the target angle of the active wheels. Then aiming at the smoothness of the dynamic switch, the active wheel angle trajectory was constructed based on the B-spline theory.

The research and development of data-driven highly automated driving system components such as trajectory prediction, motion planning, driving test scenario generation, and safety validation all require large amounts of naturalistic vehicle trajectory data. Therefore, a variety of data collection methods have emerged to meet the growing demand. Among these, camera-equipped drones are gaining more and more attention because of their obvious advantages. Specifically, compared to others, drones have a wider field of bird's eye view, which is less likely to be blocked, and they could collect more complete and natural vehicle trajectory data. Besides, they are not easily observed by traffic participants and ensure that the human driver behavior data collected is realistic and natural. In this paper, we present a complete vehicle trajectory data extraction framework based on aerial videos. It consists of three parts: 1) objects detection, 2) data association, and 3) data cleaning.

Autonomous driving related technologies have become a hot topic in academia and industry. Planning control is one of the core technologies of autonomous driving, which is conducive to vehicles safe and efficient driving. This paper proposes a novel optimal speed control algorithm, which considers the power system's energy consumption, the speed limit on the road, and the safe distance of the vehicle in front. An optimal speed control model of “From battery to wheel” energy consumption is established by constructing a performance index function based on the best-fitting formula of motor power, motor speed and torque. Based on the optimal control principle, the fourth-order ordinary differential equation of the speed control model is established, based on the indirect adjoining approach, the speed control model under the restriction of the road speed limit and safe distance of the preceding vehicle is derived and the analytical expression is obtained.

Low-frequency vibration caused by road roughness while driving is transmitted to the human body through tires, suspension, and seats. Prolonged exposure of the human body to the vibratory environment will have an impact on ride comfort or even health issues. In order to investigate the vibration response of various segments of occupants while driving, a 15-DOF multi-body dynamic model depicting the shanks with feet, thighs, pelvis, torso with arms, and the head of occupants is established in the two-dimensional sagittal plane, which considers the contact between the occupant and the cushion, backrest headrest, and the vehicle floor simultaneously. The biodynamic parameters are obtained by fitting the published vibration experimental data based on an optimization algorithm. The previously proposed half-car model is incorporated into the human model to construct an integrated vehicle-human model for further ride comfort analysis.