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Torque Vectoring Control for distributed drive electric vehicle is studied. A handling improvement algorithm for normal cornering maneuvers is proposed based on state variable feedback control: Yaw rate feedback together with steer angle feedforward is employed to improve transient response and steady gain of the yaw rate, respectively. According to the feedback coefficient's influence on the transient response, an optimization function is proposed to obtain optimum feedback coefficients under different speeds. After maximum feedforward coefficients under different speeds are obtained from the constraint of the motor exterior characteristic, final feedforward coefficients are calculated according to an optimal steering characteristic. A torque distribution algorithm is presented to help the driver to speed up during the direct yaw moment control.

Although Hydrostatic Transmission System (HTS) had been used in many places, such as machine tools, agriculture machinery, construction machinery, and vehicles, it had not been used in good performance. Twenty years ago many people began to design new hydrostatic transmission with higher efficiency. Hydrostatic Energy Storage Transmission System (HESTS) is one of new hydrostatic transmission system with higher efficiency. HESTS is more fit for being used in vehicle that is always running in undulating ground or starting and braking frequently. Construction of vehicular HESTS was analyzed, mathematical model of vehicular HESTS was established. The needed control strategies of vehicular HESTS were analyzed because there are many variables would be controlled in the new transmission system.

To develop a free-piston engine-alternator integrative power system for Hybrid Electric Vehicles, the key design parameters, such as reciprocating mass of the piston assembly, compression ratio, the ignition timing, the engine fuel consumption rate and power output, are studied based on the simulation. The results show that, the system simulation model of the free piston engine can predict the in-cylinder pressure vs. the piston's displacement being accurate enough as the test results from reported reference. The model can be employed to optimize the design parameters and to predict the fuel economy and power output. It provides the methods and bases for the free piston engine design and predicting the main performance parameters' values.

In this paper the approach of using modal parameters to detect and locate damage of automobile rear axle under experimental condition is explained. This method uses the changes in the curvature mode of the structure as the damage identification indicator to detect and locate damage. The curvature mode and the damage identification indicator are explained, the process of the identification is introduced. The method is demonstrated with a FEM (Finite Element Method) analysis on a plate under different damage conditions. And the indicator is improved with a weighting function. Then EMA (Experimental Modal Analysis) is conducted on a damaged and an undamaged rear axle of a vehicle to get the modal parameters for the damage identification indicator which later identifies and locates the damages, thus validating the introduced method.

Plug-in hybrid electric vehicles (PHEVs) provide significantly improvement in fuel economy over conventional vehicles as well as reductions in greenhouse gas and petroleum. Numerous recent reports regarding control strategy, power train configuration, driving pattern, all electric range (AER) and their effects on fuel consumption and electric energy consumption of PHEVs are reported. Meanwhile, the control strategy for engine start-stop and mileage between recharging events from the electricity grid also has an important influence on the petroleum displacement potential of PHEVs, but few reports are published. In this paper, a detailed simulation model is set up for a plug-in series hybrid electric vehicle (PSHEV) employing the AVL CRUISE. The model was employed to predict the AER of the baseline PSHEV using rule-based logical threshold switching control strategy.

In this paper, based on the plug-in series hybrid electric vehicle development project, the vehicle technology solutions and the match of power system parameters were analyzed. The vehicle control strategies were identified and optimized according to plug-in hybrid vehicle features. The plug-in series hybrid, rule-based logic threshold switching control strategy, charge depleting (CD) mode and charge-sustaining (CS) mode are chosen according to the key factors, such as the environment, performance requirements, technical requirements and cost. And then the structure and model of vehicle control strategy were established to carry out vehicle energy management and power system control. The parameter selection, electric drive system matching, energy storage system design based on the requirement of vehicle performance, system architecture and control strategy are presented.

Prediction and analysis of the thermo-mechanical coupling behavior in friction braking system is very important for the design and application of vehicle brakes, such as brake judder, brake squeal, brake wear, brake cracks, brake fade. This paper aims to establish a macro-structural model of the thermo-mechanical dynamics of the ventilated disc brake with asymmetrical outer and inner disc thickness, taking into account the friction-velocity curve of the disc pad couple acquired by testing. On the basis of finite elements analysis of the model, the predictions of the thermo-mechanical responses of the brake disc are presented, including disc transient temperature field and normal stress in radial, circular and axial directions, disc lateral deformation and disc thickness variation. Numerical predictions of the disc surface temperature and later distortion are compared with experimental measurements obtained by thermocouples and non-contact displacement sensors.

Idle stopping is one of the most important fuel saving methods for hybrid electric vehicle (HEV). While the enriched injection strategy which was employed to ensure reliable ignition of first cycle will leads to even more fuel film stayed in the intake port, all of the liquid film will evaporate randomly and interfere the mixture air-fuel ratio of the followed cycles. The fuel transport of the first cycle should be enhanced to reduce the residual fuel film, and then the control of the cycle-by-cycle air-fuel ratio will become easier and the combustion and HC emissions will also be better. In this paper the mixture preparation characteristics of the unfired first cycle, as well as the combustion and HC emissions characteristics of the fired first cycle under various injection timing strategies such as close-valve injection, mid-valve injection, and open-valve injection were investigated.

A cycle-resolved test system was designed in a Two Stage Direct Injection (TSDI) Gasoline engine to simulate the engine quick start process in an Integrated Start and Generator (ISG) Hybrid Electric Vehicle (HEV) system. Based on the test system, measurement of the in cylinder HC concentrations near the spark plug under different engine coolant temperature and cranking speed conditions were conducted using a Fast Response Flame Ionization Detector (FFID) with Sampling Spark Plug (SSP) fits, then the in-cylinder equivalence ratio near the spark plug was estimated from the measured HC concentrations. In addition, the effects of the 1st injection timing, 2nd injection timing, and total equivalence ratio on the mixture formation near the spark plug were analyzed by means of experiments.

Based on the experimental data of true stress-strain measured by DIC (Digital Image Correlation) combined with the data from a tensile test machine, the methodology for establishing a constitutive model for Ti40 alloy sheet is presented in this paper. The procedure is demonstrated by building the constitutive relationship for Ti40 alloy sheet. As the verification of the constitutive relationship, a force-displacement diagram is simulated by FEA (Finite Element Analysis). A comparison of force-displacement diagram obtained separately by FEA and the tensile test machine is made and the result shows that the method for establishing the constitutive relationship for Ti40 alloy sheet presented in this paper are reliable and considerately accurate.

Brake squeal shows a significant uncertainty characteristic. In this paper, a series of bench tests were carried out to study the uncertainty of brake squeal on a multi-function brake inertia dynamometer test bench. Then based on time-frequency analysis results, a creative squeal confirmation and determination method was presented, which can show the squeal variations in the domains of time, frequency and amplitude together. An uncertainty analysis method was also established, in which the statistical parameters of squeal frequency and sound pressure level (SPL), and probability density evaluation of frequency based on Quantile-Quantile Plot (QQ plot) were given. And a judgment method of the frequency doubling was devised based on numerical multiple and occurrence concurrence, as well as the uncertainty statistical analysis method considering frequency doubling. All the methods established were applied to the uncertainty analysis of brake squeal.

The undesired shifting phenomenon(USP) occurs easily under the braking or climbing conditions etc., and its impact is the discomfort to the passengers or cause of vehicle's state contrary to the driver's intention, meanwhile, the wear of the clutch and synchronizer is increased, so their lifetime are greatly shortened. To the vehicle with dual clutch transmission (DCT), undesired shifting phenomenon will lead to frequent and unnecessary actuation of synchronizer for the use of pre-engagement synchronizer in the shifting control; therefore, its occurrence should be eliminated as far as possible. In this paper, the process of the undesired shifting of the vehicle with DCT is elaborated, then the generating cause of USP is described based on directed graph.

In the hybrid brake system of electric vehicle, due to the limitation of the motor braking force when the motor is at high speed and the failure of the regenerative braking force when the motor is at low speed, there are three transitional conditions in hybrid braking: the hydraulic brake system intervenes the braking, the hydraulic brake system withdraws the braking and the regenerative braking force withdraws the braking. Due to the response speed of the hydraulic system is slower than that of the motor, there is a large braking impact (the derivative of braking deceleration) in the transitional conditions of hybrid braking, which deteriorates the smoothness and comfort in braking. Aiming at the impact caused by the poor cooperation between the hydraulic braking force and the motor braking force, a coordinated strategy of double closed-loop feedback and motor force correction is proposed in this paper.

In order to explore the generation mechanism of hot-spots on the automotive brake disc, disc tests under non-frictional thermal loads are carried out on the brake dynamometer test bench. In the tests, the oxy-acetylene flame is used as the heat source, and the distribution characteristics of the disc temperature and displacement are measured and analyzed. To confirm the mechanism of the disc deformation, a disc thermal buckling model using finite element method is established, and the key factors for the disc thermal buckling under thermal loads are further analyzed. It is found that the temperature circumferential gradient is small but the temperature radial gradient is large. The disc presents waviness deformation mode with 5th order in circumferential direction, which is the first thermal buckling mode of the disc. A method using spatial frequency spectrum has been proposed to find the critical time and load of thermal buckling.

With the development of autonomous vehicle technology, there is an increasing tendency toward the application of intelligent sensors in environment-perception system on autonomous vehicle to assist vehicle in intelligent decision making relevant to autonomous driving. As for environment-perception system, a good track management method serves as the foundation, while multi-target tracking and multi-sensor data fusion are recognized as the key. In this paper, a track management method is proposed to deal with multi-target tracking based on the target-level data of multisource environmental sensors for autonomous vehicle. The track management includes four procedures as following: track initiation; point-track association; track update; track deletion. A modified fast algorithm for data association is applied in the point-track association procedure. Afterwards Kalman filter is implemented to update the track information of target. The algorithm has got through a simulation test.

The utilization of the SLAM (Simultaneous Localization and Mapping) technique was extended from the robotics to the autonomous vehicles for achieving the positioning. However, SLAM cannot obtain the global position of the vehicle but a relative one to the start. For sake of this, a fast and accurate system was proposed to obtain both the local position and the global position of vehicles based on mono-SLAM which realized the SLAM by using monocular camera with a lower cost and power consumption. Firstly, the rough latitude and longitude of current position was obtained by using common GPS without differential signal. Then, the Mono-SLAM operated on the consecutive video frames to generate the localization and local trajectory and its accuracy was further improved by utilizing the IMU information. After that, a piece of Map centered in the rough position obtained by common GPS was downloaded from the Open Street Map.

Real-time and reliable perception of the surrounding environment is an important prerequisite for advanced driving assistance system (ADAS) and automatic driving. And vision-based detection plays a significant role in environment perception for automatic vehicles. Although deep convolutional neural networks enable efficient recognition of various objects, it has difficulty in accurately detecting special vehicles, rocks, road pile, construction site, fence and so on. In this work, we address the task of traffic scene understanding with semantic image segmentation. Both driveable area and the classification of object can be attained from the segmentation result. First, we define 29 classes of objects in traffic scenarios with different labels and modify the Deeplab V2 network. Then in order to reduce the running time, MobileNet architecture is applied to generate the feature map instead of the original models.

Being one of the most simple and basic driving scenarios, highway scenario can be one of the first scenarios to achieve autonomous driving. Both car following (CF) and lane changing (LC) are the most basic and frequent maneuver during highway driving tasks, and therefore become two key issues to focus on in recent researches about autonomous vehicle (AV). Different from conventional CF and LC researches that attach much importance to the character, psychology, perception ability, and driving experience of human drivers, more timely and accurate reactions based on fast perception and communication technology as well as the automatic actuator are hypotheses for this research. Moreover, based on these hypotheses, a modified intelligent driver model (MIDM) is proposed for AVs’ following behavior to alleviate the fluctuations caused by lane changing behaviors.

Connected and autonomous vehicles are different from traditional vehicles. The communication between vehicles (V2V) or between vehicles and infrastructures (V2I) renders it possible to convey traffic information (e.g. signal timing or speed advisory) from signal controllers to vehicles as well as vehicles to vehicles in real time. Taking this advantage, this paper aims to developing an algorithm which enables the interconnected autonomous vehicles running efficiently on arterials. A set of driving rules determining random behavior and swarm behavior of autonomous vehicles is developed based on swarm intelligence theory. Under control of these rules, each autonomous vehicle follows the same rules, which make it select target vehicle from all the optimal individuals in detection zone according to characteristics of itself, then approach to the target by changing lane, following former car, or accelerating.

In view of the problem of low-frequency (less than 10Hz, such as 0.5Hz, 1.15Hz, 8Hz in this paper) longitudinal vibration exists in a pure electric vehicle, modeling methods of drive-line torsion vibration system are conducted. Firstly, dynamometer test is performed, signals of motor speed and seat rail acceleration are obtained, the frequency characteristics of flutter is determined using the order analysis and time frequency analysis. Then four types of modeling and analysis are investigated facing the drive-line torsion vibration problem, including single model without electromagnetic stiffness, branch model without electromagnetic stiffness, single model considering electromagnetic stiffness and branch model considering electromagnetic stiffness. The results show that, modeling taking into account the electromagnetic stiffness and branches can reflect more low-frequency characteristics helps to reveal the low-frequency longitudinal flutter of the researched electric vehicle.