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A 2 DOF nonlinear dynamic model of the automotive wiper system is established. Complex eigenvalues are calculated based on the complex modal theory, and the system stability as well as its dependence on wiping velocity is analyzed. Bifurcation characteristics of frictional self-excited vibration and stick-slip vibration relative to wiping velocity are studied through numerical analysis. Research of nonlinear vibration characteristics under various wiping velocities is conducted by means of phase trajectories, Poincaré map and frequency spectrum. The pervasive stick-slip vibration during wiping is confirmed, and its temporal and spatial distributions are analyzed by way of time history and contour map. Duty ratio of stick vibration and statistics of scraping residual are introduced as quantitative indexes for wiping effect evaluation. Results indicate that the negative slop of frictional-velocity characteristic is the root cause of system instability.

Startup from subzero temperature is one of the major challenges for polymer electrolyte membrane fuel cell (PEMFC) to realize commercialization. Below the freezing point (0°C), water will freeze easily, which blocks the reactant gases into the reaction sites, thus leading to the start failure and material degradation. Therefore, for PEMFC in vehicle application, finding suitable ways to reach successful startup from subfreezing environment is a prerequisite. As it’s difficult and complex for experimental studies to measure the internal quantities, mathematical models are the effective ways to study the detailed transport process and physical phenomenon, which make it possible to achieve detailed prediction of the inner life of the cell. However, review papers only on cold start numerical models are not available. In this study, an extensive review on cold start models is summarized featuring the states and phase changes of water, heat and mass transfer.

In this study, the vibroacoustic characteristics and torque fluctuation of switched reluctance motors (SRMs) with different phases and poles have been analyzed in detail. Also, the common four SRMs, i.e., three-phase 6/4 SRM, four-phase 8/6 SRM, five-phase 10/8 SRM, and six-phase 12/10 SRM, have been selected. First, the spatial-temporal distribution characteristics of radial force in SRMs were revealed by virtue of the analytical derivation, which was validated by the 2D Fourier decomposition based on the finite-element results of radial force. Second, a multiphysics model, which was composed of an electromagnetic field, a mechanical field, and an acoustic field, was established to predict the noise behaviors of SRMs with different phases and poles. Third, the relationship between the torque fluctuation and the phases / poles of SRMs, and the relationship between the noise and the radial force / phases / poles are all analyzed.

To analyze the K&C (kinematics and compliance), handling and stability performance of the vehicle chassis, some simulations are usually performed using a multi-body dynamics software named ADAMS. This software introduces assumptions that simplify the components of the suspension as rigid bodies. However, these assumptions weaken the accuracy of the simulation of ADAMS. Therefore the use of flexible bodies in K&C and handling and stability simulation in ADAMS is needed to conduct more precise suspension system designs. This paper mainly analyses the influences of the subframe flexibility on handling and stability simulation in ADAMS/Car. Two complete vehicle models are built using ADAMS/Car and Hypermesh. The only difference between the two models is the subframe of the front McPherson suspension. One of the subframes is simplified as a rigid body. The other one is a flexible body built using the MNF file from Hypermesh.

The frame of a low-speed electric vehicle was treated as the research object in the paper. The fatigue load of the frame was analyzed with multi-body dynamics method and the fatigue life of frame was analyzed with the nominal stress method. Firstly, the multi-body dynamics model of the vehicle was established and the multi-body dynamics simulation was carried out to simulate the condition where the vehicle used to travel. The fatigue load history of the frame was obtained from the simulation. Secondly, the amplitude-frequency characteristic of the fatigue load was analyzed. The frequency of the fatigue load mainly focused on 0~20HZ from the analysis. Thirdly, the modal of frame was analyzed. As the frequency of the fatigue load was less than the natural frequency of the frame, the quasi-static method was selected to calculate the stress history of the frame. Next, the fatigue life of the frame was analyzed based on S-N curve.

Parallel-connected modules have been widely used in battery packs for electric vehicles nowadays. Unlike series-connected modules, the direct state inconsistency caused by parameter inconsistency in parallel modules is current and temperature non-uniformity, thus resulting in the inconsistency in the speed of aging among cells. Consequently, the evolution pattern of parameter inconsistency is different from that of series-connected modules. Since it’s practically impossible to monitor each cell’s current and temperature information in battery packs, considering cost and energy efficiency, it’s necessary to study how the parameter inconsistency evolves in parallel modules considering the initial parameter distribution, topology design and working condition. In this study, we assigned cells of 18650 format into several groups regarding the degree of capacity and resistance inconsistency. Then all groups are cycled under different environmental temperature and current profile.

Vehicle sideslip angle estimation is of great importance to the vehicle stability control as it could not be measured directly by ordinary vehicle-mounted sensors. As a result, researchers worldwide have carried out comprehensive research in estimating the vehicle sideslip angle. First, as the attitude would affect the acceleration information measured by the IMU directly, different kinds of vehicle attitude estimation methods with multi-sensor fusion are presented. Then, the estimation algorithms of the vehicle sideslip angle are classified into the following three aspects: kinematic model based method, dynamic model based method, and fusion method. The characteristics of different estimation algorithms are also discussed. Finally, the conclusion and development trend of the sideslip angle estimation are prospected.

An online fault detection and isolation (FDI) method for several common sensor faults and even demagnetization of PMSM is proposed by combining model-based and signal analysis technology. To begin with, the field reconstruction method (FRM) of PMSM is employed to obtain the flux residuals which are used as the criterion of fault detection. Then, the flux residuals are transformed by multi sequence harmonic synchronous rotating transformation and inputted into low pass filters (LPFs) in order to obtain the DC components. Last, offset and gain faults of the two phase current sensors, offset fault of the rotor angle sensor and permanent magnet (PM) demagnetization can be isolated by comparing the DC components and preset thresholds. The detection and isolation strategy of PMSM is validated by motor controller hardware in motor bench tests.

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.

As the key assembly of new energy vehicles, the noise and vibration, and harshness (NVH) performance of integrated electric drive system directly affects the driving quality of new energy vehicles. In this paper, the vibration noise characteristic test of 3in1 electric drive system is carried out in the semi-muffler chamber. In order to compare and analyze the difference between 2in1 and 3in1 electric drive system NVH performance, the power electronics unit (PEU) in the 3in1 system was removed and placed on the ground away from the platform, and vibration noise test was carried out. In order to analyze the difference of NVH performance between 2in1 status and 3in1 status, the PEU in the 3in1 system was removed and placed on the ground far away from the bench, and the NVH test was carried out. The microphone signal at 1m position and the vibration acceleration signal of the key structural surface of the system are measured experimentally.

This paper aims at the problem that the sideband vibration noise of induction motor caused by inverter pulse width modulation (PWM). The frequency distribution characteristics of the induction motor with 36 stator slots and 32 rotor slots (36/32 IM) are analyzed. Based on that, a frequency width selection method for the periodic signal-based modulation considering the characteristics of sideband electromagnetic force. Results show that this method can effectively reduce the peak value of the sound power level (SWL) of sideband noise of IM at different speeds. This method is also applicable to IMs with different pole-slot match.

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.

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.

The main challenge for future autonomous vehicles is to identify their location and body pose in real time during driving, that is, “where am I? and how will I go?”. We address the problems of pose estimation and scene perception from continuous visual frames in intelligent vehicle. Recent advanced technology in the domain of deep learning proposes to train some learning models for vehicle’s series detection tasks in a supervised or unsupervised manner, which has numerous advances over traditional approaches, mainly reflected in the absence of manual calibration and synchronization of the camera and IMU. In the paper, we propose a novel approach for pose estimation and scene recognition with a deep fusion of multi-modal neural features in the manner of unsupervised. Firstly, low-cost camera and IMU are used to extract original visual and inertial data, then the visual and inertial encoders are utilized to encoder the feature of the two modes.

Fuel cells directly convert the energy stored in hydrogen into electrical energy through an electrochemical reaction, and the only reaction product is water, which can improve the energy efficiency and reduce the pollution caused by fossil fuels. The fuel cell hybrid power system used in vehicles usually consists of a fuel cell stack and a power battery module, and the DC/DC converter is the key component to connect them together. The current ripples caused by the system have been confirmed to have detrimental effects on the fuel cell’s reliability and lifespan. In addition, it is one of the key factors that reduce the system efficiency. So, it is necessary to analyze the current ripple in the system and maintain it at a low level. In this paper, a brief review on the different kinds of converters used in vehicles has been made. Then, with the help of MATLAB/SIMULINK, a simulation model of the hybrid power system based on 4-phase interleaved parallel topology is established.

With the increasing application of turbochargers on internal combustion engines, there are more and more examples of vibration faults in turbochargers. The dynamics characteristics of the bearing-rotor system of engine turbocharger systems have received extensive attention. The bearing-rotor system dynamics is a discipline that couples bearing fluid lubrication research and rotor dynamics. The lubrication characteristics of the bearing and the dynamic characteristics of the rotor must be studied at the same time. In this paper, the lubrication model of floating ring bearing of turbocharger is established, and the viscosity lubrication condition considering heat transfer effect is obtained. Based on the Capone cylindrical bearing oil film force model, the nonlinear oil film force equation of the floating ring bearing is deduced. Further the dynamic model of the Jeffcott rotor-floating ring bearing system is established.

Intelligent and connected vehicle (ICV) and new energy vehicle (NEV) will be two important directions of the automotive technology in the future, and the coordinated development of these two directions reflects relevantly the higher requirements put forward by nowadays society and people. Through the use of intelligent and connected technology (ICT), NEVs can exchange various traffic information data with the outside world (e.g. other running vehicles, road infrastructure, internet, etc.) in real time, which is so-called Vehicle to Everything (V2X). Based on the further analysis of the mutual traffic information, the vehicles can identify the current driving conditions and predict the future driving conditions effectively, which can realize the real time optimization of the energy management strategies (EMSs) of vehicles’ powertrain system, so as to meet the driving requirements of vehicles under different driving conditions.

Deep neural network models have been widely used for environment perception of intelligent vehicles. However, due to models’ innate probabilistic property, the lack of transparency, and sensitivity to data, perception results have inevitable uncertainties. To compensate for the weakness of probabilistic models, many pieces of research have been proposed to analyze and quantify such uncertainties. For safety-critical intelligent vehicles, the uncertainty analysis of data and models for environment perception is especially important. Uncertainty estimation can be a way to quantify the risk of environment perception. In this regard, it is essential to deliver a comprehensive survey. This work presents a comprehensive overview of uncertainty estimation in deep neural networks for environment perception of intelligent vehicles.

As the electric vehicle market grows rapidly, thermal analysis related to the performance of electric drive motors has gained increasing interest. However, it is hard to obtain rotor temperature for torque correction during operation which leads to unexpected inaccurate control of motors. Rotor temperature monitoring and torque correction for IPMSM (Interior Permanent Magnet Synchronous motor) of new Energy vehicles are discussed in this paper. Considering the practical application, a low-order lumped parameter thermal network (LPTN) composed of three nodes is built for calculating the rotor temperature under different operating conditions on a 160kw IPMSM of a three-in-one electric drive. To identify the parameters of LPTN, the measurements were done on a test bench with a prototype of the three-in-one electric drive. K-type thermocouples were used to directly measure the temperature of each node.