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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.

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.

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.

This research was concerned with the use of Exhaust Gas Recirculation (EGR) improving the fuel economy over a wide operating range in a downsized boosted gasoline engine. The experiments were performed in a 1.3-Litre turbocharged PFI gasoline engine, equipped with a Low Pressure (LP) water-cooled EGR system. The operating conditions varied from 1500rpm to 4000rpm and BMEP from 2bar to 17bar. Meanwhile, the engine’s typical operating points in NEDC cycle were tested separately. The compression ratio was also changed from 9.5 to 10.5 to pursue a higher thermal efficiency. A pre-compressor throttle was used in the experiment working together with the EGR loop to keep enough EGR rate over a large area of the engine speed and load map. The results indicated that, combined with a higher compression ratio, the LP-EGR could help to reduce the BSFC by 9∼12% at high-load region and 3∼5% at low-load region.

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.

Many studies show that under diesel engine operating conditions, SCR reductant sprays will impinge on the wall of exhaust pipes. In order to understand this impinging process of SCR reductant spray, and to analyze what factors affect it, a test bench was set up by means of high speed video camera. At atmospheric pressure, SCR spray was injected on a heated metal wall, the impacts of wall temperature, injection pressure, injection height and angle on developing characteristics of SCR reductant spray after impinging on the heated wall have been researched and analyzed. The results show that the heated wall temperature has a great impact on the spray developing process, when wall temperature is lower than 405K, after water evaporated the crystallized urea will remain on the wall to block exhaust pipes. When wall temperature is higher, the atomization and evaporation of SCR reductant spray will be better, and the hydrolysis process of urea will be faster.

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.

The weight of an exhaust system on a modern vehicle is increasing because of all kinds of reasons, like engine power's increasing, more catalysts for emission control and more NVH (Noise, Vibration and Harshness) performance requirements. After the engine starting, the exhaust system was not only bearing a cyclical load from the engine, which mainly causing the vibration of the exhaust system, but also the loads from the road, which was transferred through the wheels, the suspension system and the body. Because the exhaust system always worked in these bad conditions, its structural strength, durability and life-time were analyzed in the paper, by numerical simulation and physical correlation. By discretizing the exhaust system's CAD model, a finite element model was built. After restrict the finite element model as it in a real load condition, complete the structure stress analysis and Fatigue analysis of exhaust system's hanger with FEA analysis tools.

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.

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.

Durability and performance evaluation of the ageing catalyzed continuously regenerating trap (CCRT) on solid and volatile particles from diesel bus were studied through a set of transient TSI engine exhaust particle sizer spectrometer based on on-road test. Particle characteristics under stepped steady conditions and during regeneration were discussed in detail. Under idle and stepped steady conditions, total particle number and mass Emission Rate (ER) of each test presented rising trends as speed increase. Total number ERs of all tests showed downtrend as the CCRT aging. The particle number size distributions at different ageing stage showed changing characteristics due to developing filter mechanism. Compared with baseline data, the total number reduction rates at idle condition were incremental, from 91.4% to 98.9% as the CCRT ageing. Percentages of nuclei mode concentrations took higher range from 66.6% to 89.9% compared with the baseline data, 43.2-43.7%.

Gasoline Direct Injection (GDI) engines have attracted interest as automotive power-plants because of their potential advantages in down-sizing, fuel efficiency and in emissions reduction. However, GDI engines suffer from elevated unburned hydrocarbon (HC) emissions during start up process, which are sometimes worsened by misfires and partial burns. Moreover, as the engine is cranked to idle speed quickly in HEVs (Hybrid Electric Vehicle), the transients of quick starts are more dramatically than that in traditional vehicle, which challenge the optimization of combustion and emissions. In this study, test bench had been set up to investigate the GDI engine performances for ISG (Integrated Starter and Generator) HEVs during start up process. Based on the test system, cycle-controlled of the fuel injection mass, fuel injection timing and ignition timing can be obtained, as well as the cycle-resolved measurement of the HC concentrations and NO emissions.

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.

Reducing the pumping loss, and thus, the fuel consumption of gasoline engine at part load, a two-stage intake valve lift system was implanted into a PFI engine. A corresponding engine model was set up with GT-power as well, which can simulate the effect of two-stage intake valve lift and different EGR rates on fuel economy performance and on combustion condition of a gasoline engine. Based on simulation results, the valve lift control strategy and EGR control strategy was studied in this paper. Results showed that at low engine speed, when SMALL LIFT was used, the tumble flow and the combustion process in cylinder was improved and burn time duration became shorter, resulting in higher indicated efficiency and lower fuel consumption than by LARGE LIFT. With the introduction of the exhaust gas recirculation (EGR), lower fuel consumption was acquired.