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To study the generated axial force (GAF) of the drive shaft system more accurately and effectively, this paper introduces the interval uncertainty into the research focusing on the GAF. Firstly, an interval uncertainty model for calculating the GAF is proposed based on the Chebyshev polynomials and an analytical model of the GAF. The input torque, the articulation angle, the rotation angle of the drive shaft system, the pitch circle radius (PCR) of the tripod joint and the friction coefficient are regarded as interval variables. Secondly, the upper and lower bounds of the proposed GAF model under interval uncertainty parameters are calculated quickly with the vertex method. Then the interval uncertainty optimization of the GAF under uncertainty parameters is performed. The upper bound of the response interval of the GAF is taken as the optimization object.

The characteristics of suspension elastic elements (i.e., spring, damper and anti-roll bar) are directly related to the handling and ride comfort performances, how to tune the characteristics of suspensions' elastic elements is always a big issue in developing the chassis of a vehicle. In this paper, a multi-body dynamics model of a passenger car within MSC.ADAMS® is integrated with iSight FD®, an optimization tool, to carry out a multi-objective optimization for improving the behavior of vehicle handling and ride comfort. The characteristics of suspension elastic elements (i.e., spring, damper and anti-roll bar) are considered as design variables. For handling, the objectives are defined by the measurements from multi-body dynamics simulation of typical double lane change according to ISO3888 standard. For ride comfort, the frequency-weighted RMS (Root Mean Square) value of vertical acceleration of the front seat rail according to ISO2631 standard is set as the objective.

The trajectory planning and the accurate path tracking are the two key technologies to realize the intelligent driving. The research of the steering wheel angle plays an important role in the path tracking. The purpose of this study is to optimize the steering wheel angle input during the automated lane changing. A dynamic programming approach to trajectory planning is proposed in this study, which is expected to not only achieve a quick reaction to the changing driving environment, but also optimize the balance between vehicle performance and driving efficiency. First of all, the lane changing trajectory is planned based on the positive and negative trapezoidal lateral acceleration method. In addition, the multi-objective optimization function is built which includes such indexes: lateral acceleration, lateral acceleration rate, yaw rate, lane changing time and lane changing distance.

The good mobility and large carrying capacity promote the popularity of intercity coach in mass transit, especially in the long distance passenger transport nowadays. However, accidents related to coach and bus usually involve large casualties. Higher risk of fatalities is exhibited in rollover than the other coach accident types. In order to protect the occupants when a rollover accident occurs, coach structure must have sufficient strength to resist the impact loads. This paper presents a rollover test of an intercity coach body section using both numerical simulation and experimental testing to investigate its rollover crashworthiness in accordance with ECE R66. A full scale coach body section is manufactured and a tilting bench is designed and fabricated. Displacement transducers and accelerometer are equipped to record the time history of superstructure deformation and impact acceleration. And the FE model was developed accordingly.

Current gasoline-gas vapor recovery system is incomplete, for it cannot adjust the vapor-liquid ratio automatically due to the change of working temperature. To solve this problem, this paper intends to design a new system and optimize its parameters. In this research, variables control method is used for tests while linear regression is used for data processing. This new system moves proportion valve away and adds a DSP control module, a frequency conversion device, and a temperature sensor. With this research, it is clearly reviewed that the vapor-liquid ratio should remains 1.0 from 0 °C to 20 °C as its working temperature, be changed into 1.1 from 20 °C to 25 °C, be changed into 1.2 from 25 °C to 30 °C, and be changed into 1.3 when the working temperature is above 30 °C.

An Inline 4-cylinder engine is equipped with second-order balance shafts. When the engine is running under no-load acceleration conditions, the gear system of the balance shaft generated whine noise. In this paper, an analysis and experiment method for reducing the whine noise is presented. First, a flexible multi-body dynamic model of the engine is established, which includes shaft and casing deformation, micro-modification of the gears. Taking the measured cylinder pressure as input, the load on each gear of balance shaft gear system is calculated. In addition, the influence of tooth surface micro-modification on the meshed noise was analyzed. The results show that the dynamic meshing force between the crank gear and the shim gear is large under the original tooth surface micro-modification parameters, which is the main reason of the whine noise.

For the improvement of the vehicle yaw stability, this paper studies the control problem of the active front steering (AFS) system with actuator input delay. A novel sliding mode predictive control method to handle actuator input delay is proposed for the AFS system. Firstly, considering the nonlinearities of the vehicle system, a linear parameter varying vehicle system model with two-level structure is proposed to capture the vehicle dynamic behaviors. Secondly, to deal with the issues of actuator input delay and system constraints, a novel sliding mode predictive control method is put forward. In the process of controller design, a sliding mode control algorithm is employed for the improvement of the robustness of the control system, and then a model predictive control algorithm is employed to deal with system constraints.

Electronic expansion valve as a throttle element is widely used in heat pump systems and flow characteristics are its most important parameter. The flow characteristics of the electronic expansion valve (EXV) with a valve port diameter of 3mm are studied, when the refrigerant R134a is used as the working fluid. The main factors affecting the flow characteristics are researched by adopting the orthogonal experiment method and single factor control method, for example, inlet pressure, inlet temperature, outlet pressure and valve opening. The results show that the expansion valve opening degree has the greatest influence on mass flow rate. In view of the complicated phase change of the refrigerant passing through electronic expansion valve, it is difficult to model the flow characteristics accurately.

The thermal management system, which is used to improve driving safety and thermal comfort, is one of the most important systems in electric vehicles. In recent years, researchers have coupled the heat pump system and the battery cooling system to effectively improve the heating COP (Coefficient of Performance). Therefore an accurate dynamic model of thermal management system plays a key role in investigating system performance and optimal control strategies. In this paper, an electric vehicle thermal management system based on four-way valve heat pump system is designed. The moving boundary method is improved by considering the unsteady flow of the external fluid, and then a 13-order dynamic model of the thermal management system is established. Firstly, the control equations of evaporator, condenser and chiller are derived according to the principle of conservation, and then a dynamic model of thermal management system is established in Simulink.

Uniaxial fatigue tests of rubber dumbbell specimens under different mean and amplitude of strain are carried out. An Extreme Learning Machine (ELM) model optimized by Dragonfly Algorithm (DA) is proposed to predict the fatigue life of rubber based on measured rubber fatigue life data. Mean and amplitude of strain and measured rubber fatigue life are taken as input variables and output variables respectively in DA-ELM model. For comparison, genetic algorithm (GA) and particle swarm optimization (PSO) are used to optimize ELM parameters, and GA-ELM and PSO-ELM models are established. The comparison results show that DA-ELM model performs better in predicting the fatigue life of rubber with least dispersion. The coefficients of determination for the training set and test set are 99.47% and 99.12%, respectively. In addition, a life prediction model equivalent strain amplitude as damage parameter is introduced to further highlight the superiority of DA-ELM model.

The durability road test of a vehicle is an important test to verify the reliability of vehicle components. In order to carry out the durability bench test for drive shaft systems of all-terrain vehicles, a method for acquiring time domain signals of articulation angles of the CVJ, input torque, and rotational speeds of drive shaft systems is proposed. The acquired load spectrum of drive shaft systems is preprocessed including deleting small amplitudes, de-drifting, deburring, filtering, etc. Peaks and valleys are extracted from the preprocessed load spectrum. Based on the graphic method and the estimator stabilization method, the upper and lower thresholds of the time domain extrapolation of the load spectrum are determined, and then the peaks and valleys excesses that exceed the upper and lower thresholds are extracted. The generalized pareto distribution function is used to fit the distribution of peaks and valleys excesses.

A dynamic performance calculating model for a powertrain-subframe mounting system (PSMS) is presented. Calculation methods for determining the dynamic displacements of a powertrain center of gravity (CG), the dynamic displacements of a subframe CG and the dynamic reaction forces of each mount in a PSMS under ground and motor shake excitation are developed in this paper. An optimization procedure based on the genetic algorithm and SQP is developed for reducing resonance peaks of the reaction forces at mounts. A generic PSMS with three powertrain-subframe mounts and four subframe-body mounts is used to validate the optimization method. The optimization results demonstrate that the results using the optimization procedure can effectively reduce the reaction forces at mounts.

In the automotive industry, testing the sound absorption coefficient of acoustic materials through reverberation chambers has been widely used. The advantage of this method is that sound waves are incident on the surface of acoustic materials randomly, which is more in line with actual engineering. At present, most of the reverberation chamber design and construction refers to the international standard ISO 354-2003. However, although the design indicators of the reverberation chamber have already met the requirements of the standard ISO 354-2003, there are still some differences between the test results of different reverberation chambers on the same group of samples to be tested, and sometimes the differences are so big they affect the engineering applications. In this paper, the sound absorption coefficients of the same group of samples in different reverberation chambers are tested, and there are some differences in the sound absorption coefficients.

The mount bracket is an important part of the mount system, and its dynamic characteristics will affect dynamic characteristics of the mount system, which means it will affect NVH(Noise, Vibration, Harshness) of the vehicle. Based on the large error between the test result and the finite element analysis(FEA) result, the dynamic finite element model of the mount bracket can be modified from the material parameters and the equivalent boundary of the bolt joint. In this paper, a method to identify the parameters of the mount bracket model by combining modal test, FEA, and the mathematical optimization model was presented. Firstly, based on HyperStudy platform, the optimization objective was minimizing the natural frequency error between FEA and free mode test, and the material parameters of the bracket to be identified were used as design variables to build the optimization function. The global response surface method was used for iteration to complete the identification.

Robust data association is a core problem of visual odometry, where image-to-image correspondences provide constraints for camera pose and map estimation. Current state-of-the-art visual semantic odometry uses local map points semantics, building semantic residuals associated with all classes to realize medium-term tracking of points. Considering the problem of inefficient semantic data associations and redundant semantic observation likelihood model in the visual semantic odometry, we propose a visual odometry, Local Semantic Odometry (LVSO), which is integrated with medium-term semantic constraints based on local nearest neighbor distance model.

To enhance the transient vibration performance of the vehicle at key on and key off, a method for optimizing mount parameters of a powertrain mounting system (PMS) is proposed. Uncertainties of mount parameters widely exist in a PMS, so a method for optimizing mount parameters of a PMS, which treats the mount parameters of a PMS as uncertain, is also proposed in this paper. Firstly, a 13 degrees of freedom (DOFs) model including car body with 3 DOFs, a PMS with 6 DOFs and unsprung mass with 4 DOFs is established, and the acceleration of the active side of mounts is calculated. An experiment is carried out to measure the accelerations located at active and passive sides of each mount and the accelerations of seat track. A comparison is made between the measured and estimated accelerations, and the proposed model is validated. Two optimization methods for the PMS are proposed based on the developed 13 DOFs model.