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Intelligent Transportation System (ITS) plays an important role in smart city, and accurate short-term traffic flow prediction is a significant part. At present, China’s ITS has developed rapidly, and advanced intelligent transportation systems have been built in major cities, such as Shanghai, Shenzhen and so on. With the promotion of mixed Electronic Toll Collection (ETC) and Manual Toll Collection (MTC) charging systems, the features of the traffic flow data have become richer. Traffic data recorded some information for the vehicles entering and exiting highway toll station including time, location, type, mileage, then we can use historical OD data to do traffic flow prediction, predict the corresponding future exit station traffic flow. Furthermore, due to the deep learning network’s ability to model deep complex non-linear relationship in data, researchers have paid more attention to predict traffic flow using deep learning models in recent years.

A thermo-mechanical fatigue analysis was conducted based on a coupled Finite Element Analysis (FEA) - Computational Fluid Dynamics (CFD) method on the crack failure of the exhaust manifold for an inline 4-cylinder turbo-charged diesel engine under the durability test. In the this analysis, the temperature-dependent material properties were obtained from measurements and the model was calibrated with comparison of the predicted exhaust manifold temperatures with the on-engine measurements under the same engine load condition. Temperature and stress/strain distributions in the exhaust manifold were predicted with the calibrated model. Analysis results showed that the cracks took place at locations with high plastic deformations, suggesting that the cause of the failure be thermo-mechanical fatigue (TMF). Using the equivalent plastic strain (PEEQ) as the indicator for thermal mechanical fatigue, three exhaust manifold design revisions were carried out by CAE analysis.

Accurate road friction coefficient is crucial for the proper functioning of active chassis control systems. However, road friction coefficient is difficult to be measured directly. Using the available onboard sensors, a model-based Extended Kalman filter (EKF) algorithm is proposed in this paper to estimate road friction coefficient. In the development of estimation algorithm, vehicle motion states such as sideslip angle, yaw rate and vehicle speed are first estimated. Then, road friction coefficient estimator is designed using nonlinear vehicle model together with the pre-estimated vehicle motion states. The proposed estimation algorithm is validated by both simulations and tests on a scaled model vehicle.

To improve the power and economy performance of pure electric vehicles, chaos particle swarm optimization (CPSO) algorithm is adopted in this study to optimize the parameters of the power system. The optimized parameter is then imported into CRUISE. The whole vehicle performance simulation in power system optimization for pure electric vehicle is carried out in CRUISE. Simulation results show that optimized vehicles can meet the expected dynamic performance and the driving range has been greatly improved. Meanwhile, it is also viable that the parameters of the optimal objective function can achieve the purpose of balancing the power performance and economic performance, which provides a reference for the development of vehicle power performance.

In this paper, based on our previously preliminary out-of-plane tire model, a complete out-of-plane flexible tire model is further developed by considering the variation of dimension and parameter values among different slices of the tire model. This tire model is validated via various MSC ADAMS® FTire virtual cleat tests. Especially, the cleat tests with non-zero tire camber angles and non-symmetric cleat shapes, which can better capture the out-of-plane tire properties, are included. By comparing the predicted results of the proposed tire model with FTire for various cleat tests, it shows that the complete out-of-plane flexible ring tire model is better at fully representing the actual tire properties for some complicated cleat testing scenarios.

The present paper is Part II of an investigation on the influences of the late intake valve closing (LIVC) and the early intake valve closing (EIVC) on the engine fuel consumptions at different loads and speeds. The investigation was conducted with two 1.5L turbo-charged gasoline direct injection (TGDI) engines, one with a low-lift intake cam and the other with a high-lift intake cam. The focus of this paper is the cylinder charge motion. Computational fluid dynamic (CFD) analyses were conducted on the characteristics of the cylinder charge motion for the load points 6 bar-bmep / 2000 rpm, 12 bar-bmep / 3000 rpm, and 19 bar-bmep / 1500 rpm, representing naturally aspirated and boost-mode operations without and with scavenging during the valve overlap.

In this paper, a gain-scheduling optimal control approach is proposed to enhance yaw stability of articulated commercial vehicles through active braking of the proper wheel(s). For this purpose, an optimal feedback control is used to design a family of yaw moment controllers considering a broad range of vehicle velocities. The yaw moment controller is designed such that the instantaneous tractor yaw rate and articulation angle responses are forced to track the target values at each specific vehicle velocity. A gain scheduling mechanism is subsequently constructed via interpolations among the controllers. Furthermore, yaw moments derived from the proposed controller are realized by braking torque distribution among the appropriate wheels. The effectiveness of the proposed yaw stability control scheme is evaluated through software-in-the-loop (SIL) co-simulations involving Matlab/Simulink and TruckSim under lane change maneuvers.

In this paper, a detailed three dimensional (3D) flexible ring tire model is first proposed which includes a rigid rim with thickness, different layers of discretized belt points and a number of massless tread blocks attached on the belt. The parameters of the proposed 3D tire model can be divided into in-plane parameters and out-of-plane parameters. In this paper, the relationship of the in-plane parameters between the 3D tire model and the 2D tire model is determined according to the connections among the tire components. Based on the determined relationship, it is shown that the 3D tire model can produce almost the same prediction results as the 2D tire model for the in-plane tire behaviors.

Vehicle jackknifing is generally associated with the loss of yaw stability, and is one of the most common cause of serious traffic accidents involving tractor-semitrailer combinations. In this paper, an active braking control strategy is proposed for jackknifing prevention of a tractor-semitrailer combination on a low friction road. The proposed control strategy is realized via upper-level and lower-level control structures considering braking of both the units. In the upper-level control, the required corrective yaw moments for tractor and semitrailer are generated using a PID controller aiming to reduce errors between the actual yaw rates of tractor-semitrailer and the target yaw rates deduced from a reference model. The corrective yaw moments are achieved through brake torque distribution among the tractor and semitrailer axle wheels in the lower-level control.

Vehicle tire performance is an important consideration for vehicle handling, stability, mobility, and ride comfort as well as durability. Significant efforts have been dedicated to tire modeling in the past, but there is still room to improve its accuracy. In this study, a detailed in-plane flexible ring tire model is proposed, where the tire belt is discretized, and each discrete belt segment is considered as a rigid body attached to a number of parallel tread blocks. The mass of each belt segment is accumulated at its geometric center. To test the proposed in-plane tire model, a full-vehicle model is integrated with the tire model for simulation under a special driving scenario: acceleration from rest for a few seconds, then deceleration for a few seconds on a flat-level road, and finally constant velocity on a rough road. The simulation results indicate that the tire model is able to generate tire/road contact patch forces that yield reasonable vehicle dynamic responses.

A tire may be one of the most critical and complex components in vehicle dynamics and road loads analyses because it serves as the only interface between the road surface and the vehicle. Extensive research and development activities about vehicle dynamics and tire models have been published in the past decades, but it is still not clear about the applications and parameter identification associated with all of these tire models. In this literature review study, various published tire models used for vehicle dynamics and road loads analyses are compared in terms of their modeling approaches, applications and parameters identification process and methodologies. It is hoped that the summary of this literature review work can help clarify and guide the future research and development direction about tire modeling.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

Automotive air conditioning systems are subject to constantly changing operation conditions and steady state simulations are not sufficient to describe the actual performance. The refrigerant mass migration during transient events such as clutch-cycling or start-up has a direct impact on the transient performance. It is therefore necessary to develop simulation tools which can accurately predict the migration of the refrigerant mass. To this end a dynamic model of an automotive air conditioning system is presented in this paper using a switched modeling framework. Model validation against experimental results demonstrates that the developed modeling approach is able to describe the transient behaviors of the system, and also predict the refrigerant mass migration among system components during compressor shut-down and start-up (stop-start) cycling operations.