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The adhesion control is the basic technology of active safety for the four-wheel driven EV. In this paper, a novel adhesion control method based on fuzzy logic control is proposed. The control system can maximize the adhesion force without road condition information and vehicle speed signal. Also, the regulation torque to prevent wheel slip is smooth and the vehicle driving comfort is greatly improved. For implementation, only the rotating speed of the driving wheel and the motor driving torque signals are needed, while the derived information of the wheel acceleration and the skid status are used. The simulation and road test results have shown that the adhesion control method is effective for preventing slip and lock on the slippery road condition.

In this research, the interior noise of a passenger car was measured, and the sound quality metrics including sound pressure level, loudness, sharpness, and roughness were calculated. An artificial neural network was designed to successfully apply on automotive interior noise as well as numerous different fields of technology which aim to overcome difficulties of experimentations and save cost, time and workforce. Sound pressure level, loudness, sharpness, and roughness were estimated by using the artificial neural network designed by using the experiment values. The predicted values and experiment results are compared. The comparison results show that the realized artificial intelligence model is an appropriate model to estimate the sound quality of the automotive interior noise. The reliability value is calculated as 0.9995 by using statistical analysis.

A disc-pad system is established to study impacts of surface topography on brake squeal from the perspective of statistical analysis. Firstly, surface topographies of brake disc and pad are precisely measured on the scale of micron and are statistically analyzed with a three-dimensional evaluation system. Secondly, the finite element model of brake disc and pad without surface topographies is created and verified through component free modal tests. Thereby the valid brake squeal model for complex modal analysis is built with ABAQUS. An effective method is developed to apply interface topographies to the smooth contact model, which consequently establishes sixty brake squeal models with topographies. Thirdly, impacts of surface topography on brake squeal are studied through comparison and statistical analysis of prediction results with and without topographies.

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.

During a car launch, the driving torque from driveline acts on brake disk, and may lead the pad to slip against the disk. Especially with slow brake pedal release, there is still brake torque applies on the disk, which will retard the rotation of disk, and under certain conditions, the disk and pad may stick again, so the reciprocated stick and slip can induce the noise and vibration, which can be transmitted to a passenger by both tactile and aural paths, this phenomenon is defined as brake groan. In this paper, we propose a nonlinear dynamics model of brake for bidirectional, and with 7 Degrees of Freedom (DOFs), and phase locus and Lyapunov Second Method are utilized to study the mechanism of groan. Time-frequency analysis method then is adopted to analyze the simulation results, meanwhile a test car is operated under corresponding conditions, and the test signals are sampled and then processed to acquire the features.

A passive thermal management system (TMS) using composite phase change material (PCM) for large-capacity, rectangular lithium-ion batteries is designed. A battery module consisting of six Li-ion cells connected in series was investigated as a basic unit. The passive TMS for the module has three configurations according to the contact area between cells and the composite PCM, i.e., surrounding, front-contacted and side-contacted schemes. Firstly, heat generation rate of the battery cell was calculated using the Bernardi equation based on experimentally measured heat source terms (i.e. the internal resistance and the entropy coefficient). Physical and thermal properties such as density, phase change temperature, latent heat and thermal conductivity of the composite PCM were also obtained by experimental methods. Thereafter, thermal response of the battery modules with the three TMS configurations was simulated using 3D finite element analysis (FEA) modeling in ANSYS Fluent.

In this paper, the performance simulation model of a domestic self-dumping truck was established using AVL-Cruise software. Then its accuracy was checked by the power performance and fuel economy tests which were conducted on the proving ground. The power performance of the self-dumping truck was evaluated through standing start acceleration time from 0 to 70km/h, overtaking acceleration time from 60 to 70km/h, maximum speed and maximum gradeability, while the composite fuel consumption per hundred kilometers was taken as an evaluation index of fuel economy. A L9 orthogonal array was applied to investigate the effect of three matching factors including engine, transmission and final drive, which were considered at three levels, on the power performance and fuel economy of the self-dumping truck. Furthermore, the grey relational grade was proposed to assess the multiple performance responses according to the grey relational analysis.

In this paper, the dynamic stress of the front subframe of a passenger car was obtained using modal stress recovery method to estimate the fatigue life. A finite element model of the subframe was created and its accuracy was checked by modal test in a free hanging state. Furthermore, the whole vehicle rigid-flexible coupling model of the passenger car was built up while taking into account the flexibility of the subframe. Meanwhile, the road test data was used to verify the validity of the dynamic model. On this basis, the modal displacement time histories of the subframe were calculated by a dynamic simulation on virtual proving ground consisting of Belgian blocks, cobblestone road and washboard road. By combining the modal displacement time histories with modal stress tensors getting from normal mode analysis, the dynamic stress time histories of the subframe were obtained through modal stress recovery method.

With the increasingly complex traffic environment, the vehicle AEB system needs to go through a large number of testing processes, in order to drive more safely on the road. For speeding up the development process of AEB and solve the problems of long cycle, high cost and low efficiency in AEB testing, in this paper, a millimeter wave radar turntable is built, and a high-precision detection algorithm of turntable encoder is designed, at the same time, a test method of vehicle AEB based on the detection data of radar turntable encoder is designed. The verification results show that methods described in this paper can be used to develop the vehicle AEB test algorithm efficiently.

In the face of energy and environmental problems, how to improve the economy of fuel cell vehicles (FCV) effectively and develop intelligent algorithms with higher hydrogen-saving potential are the focus and difficulties of current research. Based on the Toyota Mirai FCV, this paper focuses on the short-term speed prediction algorithm based on the back propagation neural network (BP-NN) and carries out the research on the short-term speed prediction algorithm based on BP-NN. The definition of NN and the basic structure of the neural model are introduced briefly, and the training process of BP-NN is expounded in detail through formula derivation. On this basis, the speed prediction model based on BP-NN is proposed. After that, the parameters of the vehicle speed prediction model, the characteristic parameters of the working condition, and the input and output neurons are selected to determine the topology of the vehicle speed prediction model.

Gas distribution of proton exchange membrane fuel cells (PEMFCs) is mainly decided by flow field of bipolar plate. The improper design of distributing channel, nonuniform gas flow distribution and current density distribution among different straight channels are the leading factors that could tremendously undermine the performance and life expectancy of the cell. However, there is lack of research focusing on distributing channel in straight-parallel flow field. In this work, a three-dimensional numerical model of PEMFC cathode flow field is developed with CFD method to investigate the effects of configuration type and width of the distributing channel on pressure distribution in distributing channel and on reactant flow distribution, pressure drop and concentration distribution in multiple straight channel. Effects of electrochemical reaction and formation of water on the flow distribution are taken into consideration.

Proton exchange membrane fuel cells (PEMFC), which convert the chemical energy into electrical energy directly through electrochemical reactions, are widely considered as one of the best power sources for new energy vehicles (NEV). Some of the major advantages of a PEMFC include high power density, high energy conversion efficiency, minimum pollution, low noise, fast startup and low operating temperature. The Membrane Electrode Assembly (MEA) is one of the core components of fuel cells, which composes catalyst layers (CL) coated proton exchange membrane (PEM) and gas diffusion layers (GDL). The performance of MEA is closely related to mass transportation and the rate of electrochemical reaction. The MEA plays a key role not only in the performance of the PEMFCs, but also for the reducing the cost of the fuel cells, as well as accelerating the commercial applications. Commercialized large-size MEA directly plays a major role in determining fuel cell stack and vehicle performance.

CuO-water nanofluids was utilized as heat transfer medium in the cooling system of the diesel engine. By using CFD-Fluent software, for 0.5%, 1%, 3% and 5% mass concentration of nanofluids, 3-dimensional numerical simulation about flow and heat transfer process in the cooling system of engine was actualized. According to stochastic particle tracking in turbulent flow, for solid-liquid two phase flow discrete phase, the moving track of nanoparticles was traced. By this way, for CuO nanoparticles of different mass concentration nanofliuds in the cooling jacket of diesel engine, the results of the concentration distribution, velocity distribution, internal energy variation, resident time, total heat transfer and variation of total pressure reduction between inlet and outlet were ascertained.

The noise and vibration of electric vacuum pump (EVP) become a major problem for electric vehicles when the vehicle is stationary. This paper aims at the EVP’s abnormal noise of an electric vehicle when stationary. Driver’s right ear (DRE) noise was tested and spectrogram analysis was carried out to identify the noise sources. In order to attenuate this kind of abnormal noise, a new EVP rubber mount with a segmented structure was introduced, which optimized the transfer path of vibration. Then dynamic stiffness and fatigue life of the EVP mount with different rubber hardness were calculated through finite element analysis (FEA) approach. Bench tests of fatigue life and DRE noise were performed to validate the FEA results. Test data of the sample mount shows that sound pressure level of DRE was dramatically attenuated and thus passengers’ ride comfort was enhanced.

The conducted emissions of DC motors have been a very important content when testing electromagnetic noise. It has certain practical guiding significance to optimize and improve the motor in the design stage through the simulation of conducted emissions circuit level. The existing literature research shows that the simulation results can not reflect the test results of the conducted emissions of the motor well because it is difficult to accurately model the armature winding and the commutation process of the motor in the electromagnetic simulation of the conducted emissions circuit level of the DC brush motor. In this paper, an electromagnetic simulation modeling method for conducted emissions of DC motor is proposed. The circuit model established in the PSPICE can simulate the actual conducted emissions values of DC motor by the method.

The vehicle pull problem is very important to driving safety. Major factors that may cause the pull problem related to tire include variations of geometric dimension (e.g. RPK) and stiffness (e.g. cornering stiffness, aligning stiffness), plysteer and conicity. In previous research, the influencing mechanism of these factors was well studied. But in fact, vehicle pull problem caused by tire is probabilistic. When we assemble four tires onto the car, there could be 384 different assembly arrangements. If there are significant differences among these four tires, there will also be significant differences in the influence of different tire assembly schemes on vehicle pull, which has not been systematically discussed in previous studies. If we want to evaluate the pull performance of all these arrangements by vehicle test, it will be a time consuming process which will take almost 24 working days, along with a high test expense.

Blower is one of the main noise sources of fuel cell vehicle. In this paper, a narrowband active noise control (ANC) model is established based on adaptive notch filter (ANF) to control the high-frequency noise produced by the blower. Under transient conditions, in order to reduce the frequency mismatch (FM) of ANC for blower, a new Frequency Mismatch Filtered-Error Least Mean Square algorithm (FM-FELMS) is proposed to attenuate blower noise under transient conditions. According to the theoretical analysis and simulation, the proposed algorithm has an excellent noise reduction performance at relatively high blower speed. While for the low speed working condition, the Normalized Least Mean Square (NLMS) algorithm is applied to attenuate noise. The two algorithms could be jointly utilized to control the blower noise actively.

Artificial intelligence systems are highly accepted as a technology to offer an alternative way to tackle complex and non-linear problems. They can learn from data, and they are able to handle noisy and incomplete data. Once trained, they can perform prediction and generalization at high speed. The aim of the present study is to propose a novel approach utilizing the adaptive neuro-fuzzy inference system (ANFIS) and the fuzzy clustering method for automotive ride performance estimation. This study investigated the relationship between the automotive ride performance and relative parameters including speed, spring stiffness, damper coefficients, ratios of sprung and unsprung mass. A Takagi-Sugeno fuzzy inference system associated with artificial neuro network was employed. The C-mean fuzzy clustering method was used for grouping the data and identifying membership functions.

Wireless charging system for vehicular power batteries is becoming more and more popular. As one of important issues, charging power regulation is indispensable for online control, especially when the distance or angle between chassis and ground changes. This paper proposes a novel power regulation method named Z-Source-Based Pulse-Amplitude-Modulation (ZSB-PAM), which has not been mentioned in the literatures yet. The ZSB-PAM employs a unique impedance network (two pairs of inductors and capacitors connected in X shape) to couple the cascaded H Bridge to the power source. By controlling the shoot-through state of H bridge, the input voltage to H bridge can be boosted, thus the transmitter current can be adjusted, and hence, charging current and power for batteries. A LCL-LCL resonant topology is adopted as the main transfer energy carrier, for it can work with a unity power factor and have the current source characteristic which is suitable for battery charging.

Crashworthiness is one of the most important performances of vehicles, and the front rails are the main crash energy absorption parts during the frontal crashing process. In this paper, the front rail was simplified to a thin-walled beam with a cross section of single-hat which was made of steel and aluminum. And the two boards of it were connected by riveting without rivets. In order to optimize its crashworthiness, the thickness (t), radius (R) and the rivet spacing (d) were selected as three design variables, and its specific energy absorption was the objective while the average impact force was the constraint. Considering the error of manufacturing and measurements, the parameters σs and Et of the steel were selected as the uncertainty variables to improve the design reliability. The algorithm IP-GA and the approximate model-RBF (Radial Basis Function) were applied in this nonlinear uncertainty optimization.