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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.

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.

This paper proposes a new method of predicting the sound absorption performance of polymer wool using artificial neural networks (ANN) model. Some important parameters of the proposed model have been adjusted to best fit the non-linear relationship between the input data and output data. What's more, the commonly used multiple non-linear regression model is built to compare with ANN model in this study. Measurements of the sound absorption coefficient of polymer wool based on transfer function method are also performed to determine the sound absorption performance according to GB/T18696. 2-2002 and ISO10534- 2: 1998 (E) standards. It is founded that predictions of the new model are in good agreement with the experiment results.

Fatigue behavior of aluminum alloys under multiaxial loading was investigated with both cast aluminum A356-T6 and wrought alloy 6063-T6. The dominant multiaxial fatigue crack preferentially nucleates from flaws like porosity and oxide films located near the free surface of the material. In the absence of the flaws, the cracking/debonding of the second phase particles dominates the crack initiation and propagation. The number of cracked/debonded particles increases with the number of cycles, but the damage rate depends on loading paths. Among various loading paths studied, the circle loading path shows the shortest fatigue life due to the development of complex dislocation substructures and severe stress concentration near grain/cell boundaries and second phase particles.

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.

To quickly and efficiently match the planetary gearset characteristic parameter of power-spilt hybrid vehicles so that their oil-saving potential can be maximized, this study proposes a parameter matching method that comprehensively considers energy management strategy and driving cycle based on an analysis of vehicle instantaneous efficiency. The method is used to match the planetary characteristic parameter of a power-split hybrid light truck. The relevant conclusions are compared with the influence of various planetary characteristic parameters on fuel consumption obtained through simulation under typical operating conditions. The simulation results show that the influence laws of the various planetary characteristic parameters on vehicle average efficiency are similar to those on fuel consumption. The proposed parameter-matching method based on vehicle efficiency analysis can effectively match the planetary characteristic parameter for power-split hybrid powertrains.

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.

Proton Exchange Membrane Fuel Cell (PEMFC) uses hydrogen and oxygen for fuel, the whole energy conversion process almost has no negative impact on the environment. The PEM fuel cell stack with the advantages of low-operating temperature, high current density and fast start-up ability is considered to be the next generation of new electric vehicle power. However, due to the limited current output, it is difficult for a single cell to meet the practical application requirements. The actual fuel cell stack is formed by many single cells assembled together. The assembly process is often related to load transfer, material transfer, energy exchange, multi-phase flow, electrochemical reaction and other factors. The performance of MEA (Membrane Electrode Assembly), sealing gaskets and other components will change during the assembly process, which makes the fuel cell stack assembly process more complex.

In this paper, a low-speed pre-ignition (LSPI) diagnostic strategy is designed based on the ion current signal. Novel diagnostic and re-injection strategies are proposed to suppress super-knock induced by pre-ignition within the detected combustion cycle. A parallel controller system that integrates a regular engine control unit (ECU) and CompactRIO (cRIO) from National Instruments (NI) is employed. Based on this system, the diagnostic and suppression strategy can be implemented without any adaptions to the regular ECU. Experiments are conducted on a 1.5-liter four-cylinder, turbocharged, direct-injected gasoline engine. The experimental results show two kinds of pre-ignition, one occurs spontaneously, and the other is induced by carbon deposits. Carbon deposits on the spark plug can strongly interfere with the ion current signal. By applying the ion current signal, approximately 14.3% of spontaneous and 90% of carbon induced pre-ignition cycles can be detected.

Based on the traditional heavy commercial vehicle, hydraulic hub-motor drive vehicle (HHMDV) is equipped with a hydraulic hub-motor auxiliary drive system, which makes the vehicle change from the rear-wheel drive to the four-wheel drive to improve the traction performance on low-adhesion road. In the typical operating mode of the vehicle, the leakage of the hydraulic system increases because of the oil temperature rising, this makes the control precision of the hydraulic system drop. Therefore, a temperature compensation control strategy for the assist mode is proposed in this paper. According to the principle of flow continuity, considering the loss of the system and the expected wheel speed, the control strategy of multifactor target pump displacement based on temperature compensation is derived. The control strategy is verified by the co-simulation platform of MATLAB/Simulink and AMESim.

The purpose of this study is to evaluate the impact of two-stage pilot injection parameters on the combustion and emissions of pilot diesel compression ignition natural gas (CING) engine at low load. Experiments were performed using a diesel/natural gas dual-fuel engine, which was modified from a six-cylinder diesel engine. The effect of injection timing and injection pressure of two-stage pilot diesel were analyzed in order to reduce both the fuel consumption and total hydrocarbon (HC) and carbon monoxide (CO) emissions under low load conditions. The results indicate that, because injection timing can determine the degree of pilot diesel stratification, in-cylinder thermodynamic state, and the available mixing time prior to the combustion, the combustion process can be controlled and optimized through adjusting injection timing.

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.

Due to the advantages of low weight, low emissions and good fuel economy, downsized turbocharged gasoline direct injection (GDI) engines are widely-applied nowadays. However, Low-Speed Pre-Ignition (LSPI) phenomenon observed in these engines restricts their improvement of performance. Some researchers have shown that auto-ignition of lubricant in the combustion chamber has a great effect on the LSPI frequency. To study the auto-ignition characteristics of lubricant, an innovative single droplet auto-ignition test system for lubricant and its mixture is designed and developed, with better accuracy and effectiveness. The experiments are carried out by hanging lubricant droplets on the thermocouple node under active thermo-atmosphere provided by a small “Dibble burner”. The auto-ignition process of lubricant droplets is recorded by a high-speed camera.

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.

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.