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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.

Aiming at the abnormal vibration of driver seat of a passenger car in idle condition, vibration acceleration of engine, frame and seat rail was tested to identify vibration sources. Order tracking and spectrogram analysis indicated that the second order self-excitation of engine was the main cause. To solve the problem, semi-active controlled hydraulic engine mount with air spring of which characteristics could shift between a high dynamic stiffness and a low one was applied. Then the structure and principle of the mount with variable characteristics was introduced and control mode was analyzed. Dynamic characteristics were obtained by bench test. With sample mount applied, vibration of seat rail was tested again in multiple vehicle and engine working conditions. Dates showed that abnormal vibration in idle condition was extremely reduced and the mount could also meet the requirement of engine to dynamic stiffness in driving conditions.

The current global chassis control (GCC) frequently makes use of decoupled control methods which depend on driving condition partition and simple rule-based vertical force distribution, and are insufficient to obtain optimal vehicle dynamics performance. Therefore, a novel hierarchical global chassis control system for a distributed electric vehicle (DEV), which is equipped with four wheel driving/steering and active suspension systems, is developed in this paper. The control system consists of three layers: in the upper layer, the desired forces/moments based on vehicular driving demands are determined; in the middle layer, a coordinated control method of longitudinal/lateral/vertical tire forces are proposed; in the lower layer, the driving/steering/suspension control is conducted to realize each distributed tire force.

In this paper, a model-based diagnostic system was developed to detect and isolate the dosing fault and the outlet NOx sensor fault for the SCR system. The dosing fault is treated as an actuator additive fault, while the outlet NOx sensor drift and/or offset fault is treated as a sensor additive fault. First, a 0-D SCR model was developed to facilitate the model-based approach. A parity equation residual generator was designed based on the linearized SCR model and the fault transfer function matrix. The diagnostic algorithm is then implemented in the Matlab/Simulink environment for validation. A high fidelity nonlinear 1-D SCR model is used to generate system outputs and to simulate the plant. The simulation results show that the model-based fault diagnosis system succeeds in detecting and isolating the outlet NOx sensor and dosing faults with good sensitivity and robustness

Vehicle hood styling has significant influence on headform kinematics in assessment tests of pedestrian impact protection performance. Pedestrian headform kinematics on vehicle front-end models with different hood styling characteristics is analyzed based on finite element modeling. More elevated feature lines near hood boundary and the following continuous hood surface towards fender will result in a different headform motion. It can lead to larger deformation space, more rotation and earlier rebound of the headform impactor, which will benefit the head impact protection performance. In addition, hood geometry characteristics such as hood angle and curvature have effects on structural stiffness. Therefore, inclusion of considerations on pedestrian head protection into the vehicle hood styling design stage may lead to a more effective and efficient engineering design process on headform impact analysis.

For fracture cracks that occurred in the tight coupling exhaust manifold durability test of a four-cylinder gasoline engine with EGR channel, causes and solutions for fracture failure were found with the help of CFD and FEA numerical simulations. Wall temperature and heat transfer coefficient of the exhaust manifold inside wall were first accurately obtained through the thermal-fluid coupling analysis, then thermal modal and thermoplastic analysis were acquired by using the finite element method, on account of the bolt pretightening force and the contact relationship between flange face and cylinder head. Results showed that the first-order natural frequency did not meet the design requirements, which was the main reason of fatigue fracture. However, when the first-order natural frequency was rising, the delta equivalent plastic strain was increasing quickly as well.

In order to predict the thermal fatigue life of the internal combustion engine exhaust manifold effectively, it was necessary to accurately obtain the unsteady heat transfer process between hot streams and exhaust manifold all the time. This paper began with the establishment of unsteady coupled heat transfer model by using serial coupling method of CFD and FEA numerical simulations, then the bidirectional thermal coupling analysis between fluid and structure was realized, as a result, the difficulty that the transient thermal boundary conditions were applied to the solid boundary was solved. What's more, the specific coupling mode, the physical quantities delivery method on the coupling interface and the surface mesh match were studied. On this basis, the differences between strong coupling method and portioned treatment for solving steady thermal stress numerical analysis were compared, and a more convenient and rapid method for solving static thermal stress was found.

In this paper, the relationship was investigated between objective psychoacoustic parameters, A-weighted sound pressure level (SPL) and the results of the subjective evaluation by using grey relational analysis (GRA). The sounds were recorded with eight different passenger cars at four different running conditions. The sound quality indices were calculated, including loudness, sharpness, roughness, fluctuation, and A-weighted SPL. Subjective evaluation was performed by thirty subjects using rating scale method. GRA was compared with traditional correlation analysis, and the comparison shows that some hidden information which could not be found in the traditional correlation analysis was revealed. In order to know the further relationship between fluctuation and subjective evaluation, another subjective evaluation was performed by the same 30 subjects. The result demonstrates that the relationship revealed from GRA is correct.

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.

As one of the most important auto-body moving parts, door hinge is the key point of door design and its accessories arrangement, also the premise of the door kinematic analysis. We proposed an effective layout procedure for door hinge and developed an intelligent system on CATIA CAA platform to execute it. One toolbar and five function modules are constructed - Axis Arrangement, Section, Parting Line, Kinematic, Hinge Database. This system integrated geometrical algorithms, automatically calculate the minimum clearances between doors, fender and hinges on sections to judge if the layout is feasible. As the sizes of the clearances are set to 0s, the feasible layout regions and extreme start/end points are shown in parts window, which help the engineer to check the parting line and design a new one. Our system successfully implemented the functions of five modules for the layout of door hinge axis and parting line based on a door hinge database.

The performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

To provide a feasible transitional solution from all-by-human driving style to fully autonomous driving style, this paper proposed concept and its control algorithm of a robust lane-keeping ‘co-pilot’ system. In this a semi-autonomous system, Learning based Model Predictive Control (LBMPC) theory is employed to improve system's performance in target state tracking accuracy and controller's robustness. Firstly, an approximate LTI model which describes driver-vehicle-road closed-loop system is set up and real system's deviations from the LTI system resulted by uncertainties in the model are regarded as bounded disturbance. The LTI model and bounded disturbances make up a nominal model. Secondly, a time-varying model which is composed of LTI model and an ‘oracle’ component is designed to observe the possible disturbances numerically and it is online updated using Extended Kalman Filter (EKF).

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.

Combustion behaviour and emissions characteristics of different blending ratios of diesel and gasoline fuels (Dieseline) were investigated in a light-duty 4-cylinder compression-ignition (CI) engine operating on partially premixed compression ignition (PPCI) mode. Experiments show that increasing volatility and reducing cetane number of fuels can help promote PPCI and consequently reduce particulate matter (PM) emissions while oxides of nitrogen (NOx) emissions reduction depends on the engine load. Three different blends, 0% (G0), 20% (G20) and 50% (G50) of gasoline mixed with diesel by volume, were studied and results were compared to the diesel-baseline with the same combustion phasing for all experiments. Engine speed was fixed at 1800rpm, while the engine load was varied from 1.38 to 7.85 bar BMEP with the exhaust gas recirculation (EGR) application.

In summer, when vehicle parks in direct sunlight, the closed cabin temperature would rise sharply, which affects the occupants step-in-car comfort Solar powered vehicle parking ventilation system adopts the solar energy to drive the original ventilator. Thus, the cabin temperature could be dramatically decreased and the riding comfort could be also improved. This research analyzed the modified crew cabin thermal transfer model. Then the performance of the solar powered ventilation system is analyzed and optimized combined with the power supply characteristics of the photovoltaic element. The storage and reuse of the solar power is achieved on condition that the cabin temperature could be steadily controlled. The research shows that, the internal temperature is mainly affected by the solar radiation intensity and the environment temperature.

With the increasingly serious global environmental and energy problems, as well as the increasing number of vehicles, pure electric vehicles with its advantages of environmental protection, low noise and renewable energy, become an effective way to alleviate environmental pollution and energy crisis. Due to the current pure electric vehicle power battery technology is not perfect, the range of pure electric vehicle has a great limit. Through the braking energy recovery, the energy can be reused, the energy utilization rate can be improved, and the battery life of pure electric vehicles can be improved. In this paper, a pure electric vehicle is taken as the analysis object, and the whole vehicle analysis model is built. Through the comparative analysis, based on the driver's braking intention and vehicle running state, the braking energy recovery control strategy of double fuzzy control is proposed.

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.

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.

Recreational vehicles have a lot of potential consumers in China, especially the type C recreational vehicle is popular among consumers due to its advantages, prompting an increase in the production and sales volumes. The type C vehicle usually has a higher air drag than the common commercial vehicles due to its unique appearance. It can be reduced by optimizing the structural parameters, thus the energy consumed by the vehicle can be decreased. The external flow field of a recreational vehicle is analyzed by establishing its computational fluid dynamic (CFD) model. The characteristic of the RV’s external flow field is identified based on the simulation result. The approximation models of the vehicle roof parameters and air drag and vehicle volume are established by the response surface method (RSM). The vehicle roof parameters are optimized by multi-objective particle swarm optimization (MO-PSO).