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The energy management strategies (EMS) for hybrid electric vehicles (HEV) have a great impact on the fuel economy (FE). The Pontryagin's minimum principle (PMP) has been proved to be a viable control strategy for HEV. The optimal costate of the PMP control can be determined by the given information of the driving conditions. Since the full knowledge of future driving conditions is not available, this paper proposed a dynamic optimization method for PMP costate without the prediction of the driving cycle. It is known that the lower fuel consumption the method yields, the more efficiently the engine works. The selection of costate is designed to make the engine work in the high efficiency range. Compared with the rule-based control, the proposed method by the principle of Hamiltonian, can make engine working points have more opportunities locating in the middle of high efficiency range, instead of on the boundary of high efficiency range.

The vehicle chassis integrated control system can improve the stability of vehicles under extreme conditions using tire force allocation algorithm, in which, the nonlinearity and uncertainty of tire-road contact condition need to be taken into consideration. Thus, An MPC (Model Predictive Control) controller is designed to obtain the additional steering angle and the additional yaw moment. By using a robust optimal allocation algorithm, the additional yaw moment is allocated to the slip ratios of four wheels. An SMC (Sliding-Mode Control) controller is designed to maintain the desired slip ratio of each wheel. Finally, the control performance is verified in MATLAB-CarSim co-simulation environment with open-loop manoeuvers.

The interaction of fuel sprays and in-cylinder flow in direct-injection engines is expected to alter kinetic energy and integral length scales at least during some portions of the engine cycle. High-speed particle image velocimetry was implemented in an optical four-valve, pent-roof spark-ignition direct-injection single-cylinder engine to quantify this effect. Non-firing motored engine tests were performed at 1300 RPM with and without fuel injection. Two fuel injection timings were investigated: injection in early intake stroke represents quasi-homogenous engine condition; and injection in mid compression stroke mimics the stratified combustion strategy. Two-dimensional crank angle resolved velocity fields were measured to examine the kinetic energy and integral length scale through critical portions of the engine cycle. Reynolds decomposition was applied on the obtained engine flow fields to extract the fluctuations as an indicator for the turbulent flow.

In the current work, unidirectional (UD) carbon fiber composite hatsection component with two different layups are studied under dynamic three-point bending loading. The experiments are performed at various impact velocities, and the effects of impactor velocity and layup on acceleration histories are compared. A macro model is established with LS-DYNA for a more detailed study. The simulation results show that the delamination plays an important role during dynamic three-point bending test. Based on the analysis with a high-speed camera, the sidewall of hatsection shows significant buckling rather than failure. Without considering the delamination, the current material model cannot capture the post-failure phenomenon correctly. The sidewall delamination is modeled by assumption of larger failure strain together with slim parameters, and the simulation results of different impact velocities and layups match the experimental results reasonably well.

Using highly efficient powertrain is one of the most important and effective approaches to increase the driving distance of electric vehicles (EVs). In this paper, a novel two-speed dual-clutch transmission (DCT) is proposed. The transmission is comprised of two traditional friction clutches and two-stage planetary gear sets. One clutch connects the input sun gear and the other connects the input carrier. The Simulink models including an electric motor and two-speed DCT are established. Gearshift schedule based on fuzzy logic which reflects the driver’s intensions is adopted to improve the dynamic and economic performance of the novel transmission. The simulation model is built using MATLAB/Simulink® to validate the effectiveness of the proposed gearshift schedule compared with the conventional two-parameter gearshift schedule. Simulation results show that both the dynamic and economic performance of the novel DCT for EVs are improved with the proposed fuzzy logic gearshift schedule.

With the rapid development of series-parallel hybrid electric vehicles (SPHEVs), mode transition from pure electrical drive to hybrid drive has attracted considerable attention. The presence of time delay due to response capacity of actuators and signal transmission of communication may cause decrease of speed tracking accuracy, even instable dynamics. Consequently, drivability of the SPHEV is unacceptable, and durability of the components is reduced. So far, plenty of control strategies have been proposed for mode transition, however, no previous research has been reported to deal with the time delay during mode transition. In this paper, a dynamic model with time delay of hybrid electric system is established. Next, a mode transition time-delay controller is proposed based on a two degree of freedom internal model controller (2-DOF-IMC).

The transient characteristics of combustion and emissions during the engine start up at different higher cranking speeds for hybrid electric vehicle (HEV) applications were presented in this paper. Cycle-by-cycle analysis was done for each start up case. Intake air mass during the first several cycles decrease as the engine was cranked at higher speed. Ignition timing is delayed with higher cranking speed, which leads to an increase of exhaust temperature. For various start up cases, similar quantity of fuel is injected at the first cycle, but the ignition timing is significantly delayed to meet the acceleration requirement when cranking speed enhanced. Because of the deterioration of intake charge, the air-fuel mixture is over-enriched in the first several cycles for the cases at higher cranking speed. With cranking speed is increased, the in-cylinder residual gas fraction rises, which leads to poor combustion and decrease of mass fraction of burned fuel.

Vehicle lateral states such as lateral distance at a preview point and heading angle are indispensable for lane keeping control systems, and such states are normally estimated by fusing signals from an onboard vision system and inertial sensors. However, the sampling rates and measurement delays are different between the two kinds of sensing devices. Most of the conventional methods simply neglect measurement delay and reduce sampling rate of the estimator to adapt to the slow sensors/devices. However, the estimation accuracy is deteriorated, especially considering the delay of visual signals may not be constant. In case of electric vehicles, the actuators for steering and traction are motors that have high control frequency. Therefore, the frequency of vehicle state feedback may not match the control frequency if the estimator is infrequently updated. In this paper, a multi-rate estimation algorithm based on Kalman filter is proposed to provide lateral states with high frequency.

Lift-off length is defined as the distance from injector hole to the location where flame stabilized on a high injection pressure direct injection (DI) diesel spray. In this paper we used the high-speed (40 kHz) Schlieren and time-averaged OH chemiluminescence imaging technique to simultaneously measure the flame lift-off locations on a DI diesel spray in an optically accessible and constant-volume combustion vessel. The time-resolved development of the diesel spray acquired from the high-speed Schlieren imaging system enabled us to observe the instantaneous spray structure details of the spray flames. The OH chemiluminescence image obtained from a gated, intensified CCD video camera with different delay and width settings was used to determine the quiescent lift-off length. Experiments were conducted under various ambient temperatures, ambient gas densities, injection pressures and oxygen concentrations.

The wedge clutch takes advantages of small actuation force/torque, space-saving and energy-saving. However, big challenge arises from the varying self-reinforced ratio due to the varying friction coefficient inevitably affected by temperature and wear. In order to improve the smoothness and synchronization time of the slipping process of the wedge clutch, this paper proposes a self-tuning PID controller based on Lyapunov principle. A new Lyapunov function is developed for the wedge clutch system. Simulation results show that the self-tuning PID obtains much less error than the conventional PID with fixed gains. Moreover, the self-tuning PID is more adaptable to the variation of the friction coefficient for the error is about 1/5 of the conventional PID.

Electric vehicles (EVs) have become a hot research topic due to the petroleum crisis and air pollution issues, and Hybrid EVs (HEVs) equipped with engines and motors are popular nowadays due to their advantage over Pure EVs. The energy distribution between the engine and the motor is the major task of the control strategy or energy management for HEVs. Rule-based and optimization-based approaches are developed in this area, but not much work has been done for large-size super-capacitor (SC) equipped HEVs, like Hybrid buses. In this paper, a new optimization-based control strategy for a hybrid bus equipped with SCs as the energy regeneration system is presented. Considering the driving patterns of a bus that is of frequent accelerations and decelerations, it is proposed to characterize each time instant by its speed and acceleration, and the energy distribution is optimized based on these two state variables.

The turbulent in-cylinder air flow and the unsteady high-pressure fuel injection lead to a highly transient air fuel mixing process in spark-ignition direct-injection (SIDI) engines, which is the leading cause for combustion cycle-to-cycle variation (CCV) and requires further investigation. In this study, crank-angle resolution particle image velocimetry (PIV) was employed to simultaneously measure the air flow and fuel spray structure at 1300 rpm in an optically accessible single-cylinder SIDI engine. The measurement was conducted at the center tumble plane of the four-valve pent-roof engine, bisecting the spark plug and fuel injector. 84 consecutive cycles were recorded for three engine conditions, i.e. (1) none-fueled motored condition, (2) homogeneous-charge mode with start of injection (SOI) during intake (50 crank-angle degree (CAD) after top dead center exhaust, aTDCexh), and (3) stratified-charge mode with SOI during mid compression (270 aTDCexh).

Recently, all world countries facing the stringent emission regulations have been encouraged to explore the clean fuel. The diesel from indirect coal liquefaction (DICL) has been verified that can reduce the soot and NOx emissions of compression-ignition engine. However, the atomization characteristics of DICL are rarely studied. The aim of this work is to numerically analyze the inner nozzle flow and the atomization characteristics of the DICL and compare the global and local flow characteristics of the DICL with the NO.2 diesel (D2) at engine conditions. A surrogate fuel of the DICL (a mixture of 72.4% n-dodecane and 27.6% methylcyclohexane by mass) was built according to its components to simulate the atomization characteristics of the DICL under the high-temperature and high-pressure environment (non-reacting) by the Large Eddy Simulation (LES).

Euro VI emission standards have set a very strict limitation on particulate matter emissions of Gasoline Direct Injection (GDI) engine. It is difficult for GDI engine to meet the Euro VI PN regulation (6×1011#/km) without a series of complicated after-treatment devices such as Gasoline Particulate Filter (GPF). Previous research shows that GDI vehicles under cold start condition account for more than 50% of both particle number and mass emissions during the entire NEDC driving cycle. Dual Injection Gasoline engine is based on the GDI engine by adding a set of port fuel injection system. The good mixing characteristics of the port fuel injection system can help to reduce the particulate matter emissions of the GDI engine during the cold start condition.

Multi-spark discharge (MSD) ignition is widely used in high-speed internal combustion engines such as racing cars, motorcycles and outboard motors in attempts to achieve multiple sparks during each ignition. In contrast to transistor coil ignition (TCI) system, MSD system can be greatly shortened the charging time in a very short time. However, when the engine speed becomes higher, the ignition will be faster, electrical energy stored in the ignition system will certainly become less, especially for MSD system. Once the energy released into the spark plug gap can’t be guaranteed sufficiently, ignition will become more difficult, and it will get worse in some harsh environment such as strong turbulence or lean fuel conditions. With these circumstances, the risks of misfire and partial combustion will increase, which can deteriorate the power outputs and exhaust emissions of internal combustion engine.

Percussive riveting is a widely used way of fastening in the field of aircraft assembly, which used to be done manually. Nowadays, replacing the traditional percussive riveting with automated percussive riveting becomes a trend worldwide, which improves the quality of riveting significantly. For the automated riveting system used in aircraft assembly, reliability is of great importance, deserving to be deeply researched and fully enhanced. In this paper, a high reliable automated percussive riveting system integrated into a dual robot drilling and riveting system is proposed. The riveting system consists of the hammer part and the bucking bar part. And both parts have been optimized to enhance the reliability. In the hammer side, proximity switches are fully used to detect the state of rivet insertion.

The numerical simulation of ice melting process on an iced helicopter rotor blade is presented. The ice melting model uses an enthalpy-porosity formulation, and treats the liquid-solid mushy zone as a porous zone with porosity equal to the liquid fraction. The ice shape on the blade section is obtained by the icing code with a dynamic mesh module. Both of the temperature change and the ice-melting process on the rotor blade section surface are analyzed. The phenomenon of ice melting is analyzed through the change of temperature and liquid fraction on the abrasion/ice interface. The liquid fraction change as with time on the abrasion/ice surface is observed, which describes the ice-melting process well. The numerical results show that the ice melting process can be simulated effectively by the melting model. The de-icing process can be monitored by observing the change of the liquid fraction of the area around the abrasion/ice interface.

Sound quality of vehicle interior noise affects passenger comfort. In order to improve the sound quality of a micro commercial vehicle, the vehicle interior noise under different conditions such as idle, constant speeds and accelerating is recorded by using artificial head with dual microphones. The sound quality of recorded noise is evaluated in both objective and subjective ways. Physical parameters of interior noise are calculated objectively, and annoyance score is analyzed subjectively using paired-comparison method. According to the regression analyzing of the annoyance score and the physical parameters, an objective evaluation parameter of the sound quality is employed. To analyze the vehicle body panel contribution to interior noise sound quality, the location and spectrum characteristics of major panel emission noise sources are identified based on partial singular valued decomposition (PSVD) method.

In recent years, with the increase of traffic accidents and traffic jams, lane change, as one of the most important and commonly automatic driving operations for autonomous vehicles, is receiving attention in academia. It is considered to be one of the important solutions that play an important role in improving road traffic safety and efficiency. However, most existing lane-changing models are rule-based lane-changing models. These models only assume a one-direction impact of surrounding vehicles on the lane-changing vehicle. In fact, lane change is a process of mutual interaction between vehicles due to the complexity and uncertainty of the traffic environment. Moreover, the safety and efficiency of existing lane-changing decision algorithms need to be improved. In this paper, we proposed a multivehicle cooperative control approach with a distributed control structure to control the model.

Precise trajectory prediction of surrounding vehicles is critical for decision-making of autonomous vehicles, and learning-based approaches are well recognized for the robustness. However, state-of-the-art learning-based methods ignore (1) the feasibility of the vehicle’s multimodal state information for prediction and (2) the mutually exclusive relationship between the global traffic scene receptive fields and the local position resolution when modeling vehicles’ interactions, which may influence prediction accuracy. Therefore, we propose a “vehicle descriptor”-based long short-term memory (LSTM) model with the dilated convolutional social pooling (VD+DCS-LSTM) to cope with the above issues.