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At present, the active safety and stability of heavy vehicles have becoming big concern among the road transportation industry. The purpose of this paper is to specify the research stability and safety of heavy vehicles those set up the accurate and reliable dynamic vehicle reference model and search the method to improve the stability and safety of tractor and semitrailer. A Multi-objective control algorithm was studied to differential braking based on linear quadratic regulator (LQR) control method. Simulation results show that the multi-objective control algorithm can effectively improve the vehicle driving stability and safety.

This paper proposed a novel fault-tolerant control method based on control allocation via dynamic constrained optimization for electric vehicles with XBW systems. The total vehicle control command is first derived based on interpretation on driver's intention as a set of desired vehicle body forces, which is further dynamically distributed to the control command of each actuator among vehicle four corners. A dynamic constrained optimization method is proposed with the cost function set to be a linear combination of multiple control objectives, such that the control allocation problem is transformed into a linear programming formulation. An analytical yet explicit solution is then derived, which not only provides a systematic approach in handling the actuation faults, but also is efficient and real-time feasible for in-vehicle implementation. The simulation results show that the proposed method is valid and effective in maintaining vehicle operation as expected even with faults.

This paper proposes a novel allocation-based control method for four-wheel independently actuated electric vehicles. In the proposed method, both actuator dynamics and input/output constraints are fully taken into consideration in the control design. First, the actuators are modeled as first-order dynamic systems with delay. Then, the control allocation is formulated as an optimization problem, with the primary objective of minimizing errors between the actual and desired control outputs. Other objectives include minimizing the power consumption and the slew rate of the actuator outputs. As a result, this leads to frequency-dependent allocation that reflects the bandwidth of each actuator. To solve the optimization problem, an efficient numerical algorithm is employed. Finally the proposed control allocation method is implemented to control a four-wheel independently actuated electric vehicle.

This paper presents a fault-tolerant control (FTC) algorithm for four-wheel independently driven and steered (4WID/4WIS) electric vehicle. The Extended Kalman Filter (EKF) algorithm is utilized in the fault detection (FD) module so as to estimate the in-wheel motor parameters, which could detect parameter variations caused by in-wheel motor fault. A motion controller based on sliding mode control (SMC) is able to compute the generalized forces/moments to follow the desired vehicle motion. By considering the tire adhesive limits, a reconfigurable control allocator optimally distributes the generalized forces/moments among healthy actuators so as to minimize the tire workloads once the actuator fault is detected. An actuator controller calculates the driving torques of the in-wheel motors and steering angles of the wheels in order to finally achieve the distributed tire forces. If one or more in-wheel motors lose efficacy, the FD module diagnoses the actuator failures first.

With the development of the advanced driver assistance system and autonomous vehicle techniques, a precise description of the driver’s steering behavior with mathematical models has attracted a great attention. However, the driver’s steering maneuver demonstrates the stochastic characteristic due to a series of complex and uncertain factors, such as the weather, road, and driver’s physiological and psychological limits, generating negative effects on the performance of the vehicle or the driver assistance system. Hence, this paper explores the stochastic characteristic of driver’s steering behavior and a novel steering controller considering this stochastic characteristic is proposed based on stochastic model predictive control (SMPC). Firstly, a search algorithm is derived to describe the driver’s road preview behavior.

In order to understand the flow and wind noise characteristics generated by the outside rearview (OSRV) mirror, a series of wind noise measurements for two production mirrors was conducted at the GM Aerodynamics Lab (GMAL) wind tunnel. These measurements included the time-averaged static pressures, surface noise sources, and far field propagation noise. The data obtained in this investigation will be used for future CFD numerical validations. The two mirrors chosen for the test are the GMT360 (a truck mirror) and the GMX320 (a sedan mirror). The test mirror was mounted on an elevated table which was specially designed for the current project to avoid any significant flow boundary layer buildup on the wind tunnel floor. The test conditions reported in this paper include four inlet speeds of 30, 50, 70 and 90 mph at 0 yaw angle. To record the wind noise sources, nine surface flush-mount microphones were used.

This paper describes a computational and experimental effort to document the detailed flow field around a pickup truck. The major objective was to benchmark several different computational approaches through a series of validation simulations performed at Clemson University (CU) and overseen by those performing the experiments at the GM R&D Center. Consequently, no experimental results were shared until after the simulations were completed. This flow represented an excellent test case for turbulence modeling capabilities developed at CU. Computationally, three different turbulence models were employed. One steady simulation used the realizable k-ε model. The second approach was an unsteady RANS simulation, which included a turbulence closure model developed in-house. This simulation captured the unsteady shear layer rollup and breakdown over the front of the hood that was expected and seen in the experiments but unattainable with other off-the-shelf turbulence models.

Computational Fluid Dynamics (CFD) has gained popularity as a tool for many airflow situations including road vehicle aerodynamics. This trend, to bring CFD to bear on vehicle aerodynamic design issues, is appropriate and timely in view of the increasing competitive and regulative pressures being faced by the automotive industry. For a large portion of the engineering community, the primary source of CFD capabilities is through the purchase of commercial CFD codes. This paper summarizes the results of a series of benchmark external aerodynamic simulations that were carried out for a generic pickup truck model using two commercial CFD codes, namely Fluent and the PowerFLOW. For direct comparisons the computations and the experiments were performed for the same model (vehicle) geometry and under similar flow conditions.

Joint failure, e.g. resistance spot weld (RSW) joint failure, has been identified as one of the key failure modes when vehicle crash occurs. Currently, a beam element or a rigid link is commonly used to represent a RSW in a full vehicle analysis. Several failure criteria have been implemented in the math-based tools to model the spot weld failure, namely the failure strain and the resultant force based failure criterion. The former is not robust and the latter requires a lot of tests to be done for different designs of the resistance spot welded joints. In the case when the RSW joint has pullout failure, i.e. the failure occurs in the base metal, a material model is used in the present work to model the RSW joint pullout failure by modeling the failure of the base material. Only simple tensile tests are needed in order to use this method while the geometry effects of the joint design and the strain rate dependence of the base material are handled by the material model itself.

One way to achieve low temperature regeneration on diesel particulate traps is to employ NO2 as the oxidant. However, the engine may not produce sufficient NOx to achieve the required particulate regeneration. An RRT (rolling regeneration trap) was proposed as a way to enhance the effective concentration in diesel engine exhaust. The RRT uses catalyzed ceramic foam, which allows repeated use of existing NOx in the exhaust stream. The ceramic foam is a filter itself: thus, it can reduce the particulate loading on the wall-flow filter, which is more prone to plugging by the particulate deposits. Furthermore, the presence of particulate matter in the catalyzed section circumvents the high temperature limit imposed by thermodynamic equilibrium of a simple NO+NO2 +O2 system. However, experimental results revealed that the regeneration efficiency on the wall-flow section was very low and NO2 slip is an issue.

Simple devices have been shown to be capable of tailoring the flow field around a vehicle and reducing aerodynamic drag. An experimental and computational investigation of a drag reduction device for bluff bodies in ground proximity has been conducted. The main goal of the research is to gain a better understanding of the drag reduction mechanisms in bluff-body square-back geometries. In principle, the device modifies the flow field behind the test model by disturbing the shear layer. As a consequence, the closure of the wake is altered and reductions in aerodynamic drag of more than 20 percent are observed. We report unsteady base pressure, hot-wire velocity fluctuations and Particle Image Velocimetry (PIV) measurements of the near wake of the two models (baseline and the modified models). In addition, the flows around the two configurations are simulated using the Reynolds Averaged Navier-Stokes (RANS) equations in conjunction with the V2F turbulence model.

LiDAR sensors have played more and more important role on Intelligent and Connected Vehicles (ICV) and Advanced Driver Assistance Systems (ADAS) .However, the development and testing of LiDAR sensors under real driving environment for ADAS applications are greatly limited by various factors, and often are impossible due to safety concerns. This paper proposed a novel functional LiDAR model under virtual driving environment to support development of LiDAR-based ADAS applications under early stage. Unlike traditional approaches on LiDAR sensor modeling, the proposed method includes both geometrical modeling approach and physical modeling approach. While geometric model mainly produces ideal scanning results based on computer graphics, the physical model further brings physical influences on top of the geometric model. The range detection is derived and optimized based on its physical detection and measurement mechanism.

The tire mechanics characteristics are essential for analysis and control of vehicle dynamics. Basically, the effects of sideslip, longitudinal slip, camber angle and vertical load are able to be represented accurately by current existing tire models. However, the research of velocity effects for tire forces and moments are still insufficient. Some experiments have demonstrated that the tire properties actually vary with the traveling velocity especially when the force and moment are nearly saturated. This paper develops an enhanced brush tire model and the UniTire semi-physical model for tire forces and moments under different traveling velocities for raising need of advanced tire model. The primary effects of velocity on tire performances are the rubber friction distribution characteristics at the tire-road interface.

According to the vehicle’s driving conditions, electronically controlled air suspension (ECAS) systems can actively adjust the height of vehicle body, so that better ride comfort and handling stability will be achieved, which can’t be realized by traditional passive suspension. This paper presents a design and implementation of ECAS controller for vehicle. The controller is aimed at adjusting the static and dynamic height of the vehicle. To exactly track the height of the vehicle and satisfy the control demand of air suspension, a height sensor decoding circuit based on the inductance sensor is designed. Based on it, a new height control algorithm is adopted to achieve rapid and precise control of vehicle height. To verify the function of the designed controller and the proposed height control algorithm, an air spring loading test bench and an ECU-in-loop simulation test bench are respectively established.

The driving range of the electric vehicle (EV) greatly restricts the development of EVs. The vehicles waste plenty of energy on account of automobiles frequently braking under the city cycle. The regenerative braking system can convert the braking kinetic energy into the electrical energy and then returns to the battery, so the energy regeneration could prolong theregenerative braking system. According to the characteristics of robustness in regenerative braking, both regenerative braking and friction braking based on fuzzy logic are assigned after the front-rear axle’s braking force is distributed to meet the requirement of braking security and high-efficient braking energy regeneration. Among the model, the vehicle model and the mechanical braking system is built by the CRUISE software. The paper applies the MATLAB/SIMULINK to establish a regenerative braking model, and then selects the UEDC city cycle for model co-simulation analysis.

This essay aims to develop an electrically controlled steering test bench and lay a solid foundation for the development of steering system. The first part mainly introduces the function, structure and working principle of the test bench. For the hardware system, it includes the steering system, fixture, sensors as well as a frameless disk motor for carrying out automatic motor input, and a dual linear motor system selected as the road resistance simulation actuator. As for the software, MATLAB/Simulink, CarSim, RTI and ControlDesk are used. Therefore, with the help of real-time simulation platform, researchers can not only build control strategy and dynamic model but also control the experiment and tune parameters in real-time. The second part of the essay aims to identify both electric and mechanical parameters of R-EPS system by carrying out tests on the proposed test bench. As parameters are successfully identified, the feasibility of the test bench is also verified.

This paper presents a fault-tolerant control (FTC) method for four-wheel independently driven and steered (4WIS/4WID) electric vehicles based on a reconfigurable control allocation to increase the flexibility for vehicle control and improve the safety of vehicle after the steering actuator fails. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle steering condition, detects and diagnoses actuator failures; 2) an upper controller that computes the generalized forces/moments to track the desired vehicle motion and trajectory; 3) a reconfigurable control allocator that optimally distributes the generalized forces/moments to four wheels. The FTC approach based on the reconfigurable control allocation reallocates the generalized forces/moments among healthy steering actuators and driving motors once the actuator failures is detected.

As one of the key technologies for EVs and HEVs, the design of their motors has been researched extensively, and some novel rotors of permanent magnet motor were proposed in order to improve torque capability, including average torque and torque ripple. Rotor structure selection of drive motor for various electric vehicles has been one of the key issues in matching of electric vehicle power system. Three motors are analyzed for providing visible insights to the contribution of different rotor structures to the torque characteristics, efficiency and extended speed range. First, an iterative comparative analysis of torque-speed characteristics with different flux linkage, d-axis inductance and rotor saliency ratio is performed for demonstrating the design principle. Then, the three motors are optimized by a genetic algorithm (GA) for further improving the torque characteristics.

The commercial vehicle is widely used in the overland transport. A prediction is given on the 9th annual China automotive industry forum that the number of the global commercial vehicles will reach eight million by the year of 2016. However, since the distance between its gravity centre and the ground is larger than that of the passenger vehicle, considering its comparatively short wheelbase, the rollover accident, which is fatal to the drivers and always makes enormous loss of merchandises, easily occurs in the case of commercial vehicles. As the number of the commercial vehicle is increasing fast, the accidents will occur more frequently, the losses will be increasingly enormous. To solve the problem, many researches about rollover early warning systems have been done. In most cases, it is assumed that the references of the vehicle are given.

This paper describes the initial phases of an on-going project in the GM Motorsports Safety Technology Research Program to investigate Indy car crashes using an on-board impact recorder as the primary data collection tool. The development of a database consisting of crash investigation data patterned after national highway crash databases is discussed. The data gathered and coded includes track and incident scene information, vehicle damage, and driver injuries, as well as the vehicle decelerations measured by the impact recorder. The paper discusses the development of specifications for the impact device, the selection of the specific recorder and its implementation on a routine basis in Indy car racing. The results from incidents that produced significant data during the 1993, 1994 and 1995 racing seasons are summarized.