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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.

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.

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.

Spray characteristics and spray wall-impingement events are the key factors for the direct injection spark ignition (DISI) engines, affecting fuel/air mixture preparation and its combustion process. Thus, the spray characteristics of a multi-hole injector for DISI engines, such as spray tip penetration and spray cone angle were investigated in an optical chamber employing the high-speed shadow photography. Furthermore, the effects of the injection pressure, ambient pressure and piston top shape on the impinging spray development were studied in the optical chamber, when the impinging distance is 26.1 mm, corresponding to about 60 CAD ATDC. In addition, the SMD and wall film thickness of the spray impinging on the piston top were studied by means of CFD technique. The results showed that the ambient pressure had the greater effect on the changes of the spray penetration and spray cone angle than the injection pressure.

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.

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.

This set combines the book Road Vehicle Dynamics with its corresponding workbook companion, Road Vehicle Dynamics: Problems and Solutions. Road Vehicle Dynamics provides a detailed overview of the dynamics of road vehicle systems, giving readers an understanding of how physical laws, human factor considerations, and design choices affect ride, handling, braking, acceleration, and vehicle safety. Chapters cover analysis of dynamic systems, tire dynamics, ride dynamics, vehicle rollover analysis, handling dynamics, braking, acceleration, total vehicle dynamics, and accident reconstruction. The workbook will enable students and professionals from a variety of disciplines to engage in problem-solving exercises based on the material covered in each chapter of that book. It presents systematic rules of analysis that students can follow in a step-by-step manner to understand the efficiencies or shortcomings of various techniques.

This workbook, a companion to the book Road Vehicle Dynamics, will enable students and professionals from a variety of disciplines to engage in problem-solving exercises based on the material covered in each chapter of that book. Emphasizing application more than theory, the workbook presents systematic rules of analysis that students can follow in a step-by-step manner to understand the efficiencies or shortcomings of various techniques. Readers will gain a greater understanding of the factors influencing ride, handling, braking, acceleration, and vehicle safety.

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.

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.

After obtaining the optimal trajectory through the lane change decision and trajectory planning, the last key technology for the automatic lane change assist system is to carry out the precise and rapid steering actuation according to the front wheel angle demand. Therefore, an automatic lane change system model including a BLDCM (brushless DC motor) model, a steering system model and a vehicle dynamics model is first established in this paper. Electromagnetic characteristics of the motor, the moment of the inertia and viscous friction etc. are considered in these models. Then, a SMC (Sliding Mode Control) algorithm for the steering system is designed to follow the steering angle input. The control torque of the steering motor is obtained through the system model according to steering angle demand. After that, the control current is calculated considering of electromagnetic characteristics of the BLDCM. Debugging and optimization of the control algorithm are done through simulations.

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.

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.

An adaptive sideslip angle observer based on discrete extended Kalman filter (DEKF) is proposed in this paper and tire-road friction adaptation is also considered. The single track vehicle model with nonlinear tire characteristics is adopted. The tire parameters can be easily obtained through road test data without using special test rig. Afterwards, this model is discretized and the maximum value of tire-road friction is modeled as the third state variable. Through the measurement of vehicle lateral acceleration and yaw rate, the tire-road adhesion coefficient can be timely updated. Simulations with experimental data from road test and driving simulator have confirmed that DEKF has very high accuracy. The convergent speed of DEKF relies on the magnitude of lateral excitation.

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.

Because of the vehicle market competitive and of the raise of customers' demanding, NVH performance became an important job, especially for new energy vehicles. As the electric vehicle moving into the direction of high speed and large torque, electric vehicle vibration and noise problems highlighted gradually. In recent years, CAE has played an increasing role in the design, development and optimization of powertrain NVH at component and system levels. The subject of this paper was the numerical and experimental evaluation of the electromagnetic and vibro-acoustic behavior of an electric powertrain. For this purpose, a coupled and fully flexible dynamics model of the electric powertrain was developed. Then electromagnetic forces including both radial and tangential force and gear mesh excitations including time-varying meshing stiffness, meshing error and meshing impact were computed, which were used to perform forced response analysis on the full FE mesh of the powertrain housing.

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.

From traditional vehicle to pure electric vehicle and then to range-extended electric vehicle (ReEV), the electrification of vehicle has caused a great change in NVH characteristics. ReEV has the most complex noise and vibration problems because it behaves both like traditional vehicle and pure electric vehicle. In addition, it has its own specific NVH characteristics. Firstly, internal combustion engine drives the generator rather than drives the vehicle. Due to the structure and load change, auxiliary power unit (APU) performs specific NVH characteristics. In addition, the pure electric mode will have the high frequency noise generated from the driveline because the noise couldn't be masked by the engine. In system level, unexpected and confusing sound in passenger compartment may affect the driver's comfort and judgments. Therefore, more and more attentions on these issues should be paid. NVH study and improvement methods on ReEV are emphasized.

Ion current sensing, which usually employs a spark plug as its sensor to obtain feedback signal from different types of combustion in SI engines, may be applied to HCCI combustion sensing instead of a prohibitively expensive piezoelectric pressure transducer. However, studies showed that the ion current detected by a spark plug sensor is a localized signal within the vicinity of the sensor's electrode gap, being affected by conditions around it. To find out better and feasible ion probe positions, a 3D-CFD model with a detailed surrogate mechanism containing 1423 species and 6106 reactions was employed to study the effect of stratification on ion distribution in HCCI combustion. The simulation results indicate that the monitor probe 1, 8 and 9 are more stable and reliable than the others. IONmax and dIONmax are more accurate to estimate CA50 and dQmax respectively.

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.