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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.

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.

An automatic tensioner with an asymmetric damping structure used in an engine front end accessory drive system is analyzed. An analytical model is established to calculate the hysteretic behavior of the tensioner. The contact characteristics of contact pairs are modeled and investigated for disclosing relation between contact pair, friction and hysteretic loop of an automatic belt tensioner. The presented models are validated by a torque measurement versus angular displacement of a tensioning arm. The errors between the calculation and the measurement are analyzed. The working torques of the tensioner during loading and unloading process are described by a bilinear hysteretic model and are written as a function with a damping ratio. The influence of damping structure parameters on the hysteretic torque is investigated. The method presented in this paper can be used for predicting the nonlinear characteristics of a tensioner before prototyping.

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.

To solve the contradiction between model complexity and the warning accuracy of the algorithm of the vehicle rollover warning, a rollover state warning method based on the secondary predictive zero-moment point position for vehicles is proposed herein. Taking a sport utility vehicle(SUV) as the research object, a linear three-degrees-of-freedom vehicle rollover dynamics model is established. On the basis of the model, the lateral position of the zero-moment point and its primary and secondary rates of change are calculated. Then, the theoretical solution of time-to-rollover of the vehicles is deduced from the lateral position of the secondary predictive zero-moment point. When the rollover warning index, the lateral position of the zero-moment point, is greater than the set threshold, the active anti-rollover control system will be triggered. The active anti-rollover braking control system adopts a hierarchical control strategy.

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.

Battery Run-down under the Electric Vehicle Operation (BREVO) model is a model that links the driver’s travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. This study implements reinforcement learning (RL) to the simplified BREVO model to optimize drivers’ decisions on charging such as charging rate, charging time, and charging capacity needed. This is done by a reward function that considers both the driver’s daily travel demands and the minimization of battery degradation over a year. It shows that using appropriate charger type (No Charge, Level 1, Level 2, direct-current Fast Charge [DCFC], extreme Fast Charging [xFC]) with an appropriate charging time can reduce battery degradation and total charging cost at the end of the year while satisfying driver’s daily travel demand.

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.

Taking a closed airbag suspension system as studying objects, the nonlinear dynamic model of the reservoir, compressor, solenoid valve, pipeline and air spring is established. The compressor exhaust volume, solenoid valve flow rate and air spring charging and discharging rate are calculated and compared with experiment to validate the model. Taking pressure difference and height adjustment rate under different working conditions of an airbag suspension as control measures, a control strategy is developed based on the established nonlinear dynamic model. The result indicates that when the vehicle is in curb weight, design weight and GVW (gross vehicle weight), the working time of the compressor can be reduced by 13.6%, 15.1% and 46.5%, respectively, compared with the conventional mode, during a height adjustment cycle. Then a state observer is proposed to estimate the steady-height for reducing the disturbance of measured height from road excitation.

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.

To solve the problems of ethnic size difference and model simplification in existing research, three kinds of lower limb finite element models of adult male with percentile 5, 50 and 95 were established based on the size characteristics of Chinese human body.The bionic reliability of the models was verified according to three different lower limb biomechanical experiments. Through the simulation analysis of pedestrian lower limb with different percentiles in side impact, it was found that in the pedestrian low-speed side impact accident, the lower percentile human body has a higher risk of lower limb injury,especially the injury of knee joint. The soft foam structure can play a better cushioning and energy absorption role in the impact process. The response parameters decrease with the decrease of percentile.In addition,the soft foam can significantly reduce the risk of lower limb injuries when impacting the lower limbs laterally at low speed.

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.

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.

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.

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 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.

Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme.

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.

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.

Bumper systems are vital to improving automotive passive safety and reducing the maintenance cost in low-speed collision. Automotive companies need to develop bumpers with adequate strength, high energy absorption rate, minimum weight and least expense. To shorten the product development period and lower the development cost, four evaluation conditions were proposed to assess the behaviors of car front bumpers based on the three main low-speed collision regulations of the US Part 581, the Canadian CFVSS215 and the European ECE-R42. A finite element method was put forward to model the car front bumper and to analyze the low-speed collision performance of the bumper system. A drop hammer impact test was carried out to verify the validity of the method, and experiment results indicated the correctness of the finite element model.