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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.

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.

Controlled Auto-Ignition (CAI) combustion can effectively improve the thermal efficiency of conventional spark ignition (SI) gasoline engines, due to shortened combustion processes caused by multi-point auto-ignition. However, its commercial application is limited by the difficulties in controlling ignition timing and violent heat release process at high loads. Stratified flame ignited (SFI) hybrid combustion, a concept in which rich mixture around spark plug is consumed by flame propagation after spark ignition and the unburned lean mixture closing to cylinder wall auto-ignites in the increasing in-cylinder temperature during flame propagation, was proposed to overcome these challenges.

Homogeneous charge compression ignition (HCCI) combined with high compression ratio is an effective way to improve engines’ thermal efficiency. However, the severe thermodynamic conditions at high load may induce knocking combustion thus damage the engine body. In this study, advanced compression ignition knocking characteristics were parametrically investigated through RCM experiments and simulation analysis. First, the knocking characteristics were optically investigated. The experimental results show that there even exists detonation when the knock occurs thus the combustion chamber is damaged. Considering both safety and costs, the effects of different initial conditions were numerically investigated and the results show that knocking characteristics is more related to initial pressure other than initial temperature. The initial pressure has a great influence on peak pressure and knock intensity while the initial temperature on knock onset.

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.

Combustion closed-loop control is now being studied intensively for engineering applications to improve fuel economy. Currently, combustion closed-loop feedback control is usually based on the cylinder pressure signal, which is the most direct and exact signal that reflects engine working process. Although there were some relatively cheap types of in-cylinder pressure sensors, cylinder pressure sensors have not been widely applied because of their high price now. Moreover, the combustion analysis based on cylinder pressure imposes high requirements on the information acquisition capability of the current ECU, such as high acquisition and analog-digital conversion frequency and so on. For developing a low price and feasible technology, a new engine information feedback method based on model calculation and crank angular velocity measurement was proposed. A simplified combustion model was operated in ECU for the real-time calculation of cylinder pressure and combustion parameters.

Engine knock is an abnormal phenomenon, which places barriers for modern Spark-Ignition (SI) engines to achieve higher thermal efficiency and better performance. In order to trigger more controllable knock events for study while keeping the knock intensity at restricted range, various spark strategies (e.g. spark timing, spark number, spark location) are applied to investigate on their influences on knock combustion characteristics and pressure oscillations. The experiment is implemented on a modified single cylinder Compression-Ignition (CI) engine operated at SI mode with port fuel injection (PFI). A specialized liner with 4 side spark plugs and 4 pressure sensors is used to generate various flame propagation processes, which leads to different auto-ignition onsets and knock development. Based on multiple channels of pressure signals, a band-pass filter is applied to obtain the pressure oscillations with respect to different spark strategies.

Lean-burn combustion is an effective method for increasing the thermal efficiency of gasoline engines fueled with stoichiometric fuel-air mixture, but leads to an unacceptable level of high cyclic variability before reaching ultra-low nitrogen oxide (NOx) emissions emitted from conventional gasoline engines. Multi-point micro-flame ignited (MFI) hybrid combustion was proposed to overcome this problem, and can be can be grouped into double-peak type, ramp type and trapezoid type with very low frequency of appearance. This research investigates the micro-flame ignition stages of double-peak type and ramp type MFI combustion captured by high speed photography. The results show that large flame is formed by the fast propagation of multi-point flame occurring in the central zone of the cylinder in the double-peak type. However, the multiple flame sites occur around the cylinder, and then gradually propagate and form a large flame accelerated by the independent small flame in the ramp type.