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In order to improve the trajectory tracking accuracy and yaw stability of vehicles under extreme conditions such as high speed and low adhesion, a coordinated control method of trajectory tracking and yaw stability is proposed based on four-wheel-independent-driving vehicles with four-wheel-steering. The hierarchical structure includes the trajectory tracking control layer, the lateral stability control decision layer, and the four-wheel angle and torque distribution layer. Firstly, the upper layer establishes a three-degree-of-freedom vehicle dynamics model as the controller prediction model, the front wheel steering controller is designed to realize the lateral path tracking based on adaptive model predictive control algorithm and the longitudinal speed controller is designed to realize the longitudinal speed tracking based on PID control algorithm.

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.

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.

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.

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 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.

Four-wheel independent drive EV is driven by four brushless DC motors which are embedded in the wheel hubs. It enables each wheel's driving torque to be controlled independently. Due to the motors' torque and rotational speed easily measured, as well as the features of fast response and precise control, the EV enjoys obvious advantages over traditional vehicles in acceleration slip regulation. In this paper a novel acceleration slip regulation strategy for four-wheel independent drive EV is studied. The strategy includes a road identification module for the peak value of road adhesion coefficient and a slip regulation logic based on PID algorithm. Through comparing the current wheel slip ratio and the utilized adhesion coefficient with the typical roads' value, the identification module adopts the fuzzy control algorithm to recognize the similarity between the current road and the typical roads. Utilizing the similarity we can calculate the optimal slip ratio of the current road.

Nowadays active collision avoidance has become a major focus of research, and a variety of detection and tracking methods of obstacles in front of host vehicle have been applied to it. In this paper, laser radars are chosen as sensors to obtain relevant information, after which an algorithm used to detect and track vehicles in front is provided. The algorithm determines radar's ROI (Region of Interest), then uses a laser radar to scan the 2D space so as to obtain the information of the position and the distance of the targets which could be determined as obstacles. The information obtained will be filtered and then be transformed into cartesian coordinates, after that the coordinate point will be clustered so that the profile of the targets can be determined. A threshold will be set to judge whether the targets are obstacles or not. Last Kalman filter will be used for target tracking. To verify the presented algorithm, related experiments have been designed and carried out.

It is known that the automobile cabin thermal comfort, could keep the driver and passengers feel better which has a great effect on traffic safety. In this paper, to the FAW truck cab, we did some researches about automobile cabin thermal comfort. Our plan is to calculate the air flow distribution and the temperature in steady and transient state when there is warm or cool air flow. The heating and cooling experiment methods standard of cabin are based on the national standard and the automobile industry standard of China. Then the numerical simulation process becomes very important. So we used the commercial CFD code- STAR-CCM+ for study in this paper. Firstly, Geometry Clean up. Secondly, Wrap and Remesh, we chose the internal surface at the wrap surface of cabin and air conditioning pipes, then we remesh the surface. Thirdly, generate the volume mesh which is polyhedral mesh, and the number of the volume mesh is 9.4 millions.

The tire lateral force is essential to the vehicle handling and stability under cornering. However, it is difficult for engineers to get the tire lateral force under high loading condition due to the limitation of loading ability for most tire test machine in the world. The widely used semi-empirical tire lateral force models are obtained by curve-fitting experiments data and thus unable to predict the load dependent lateral force. The objective of this paper is to predict the tire lateral force under high-load condition based on the low-load tire data. The nonlinear characteristics of the tire cornering stiffness with the load are greatly affected by the tire carcass compliance. In this paper, a theoretical tire lateral model was built by considering carcass complex deformation. Combined with the relationship between the half-length of the tire contact patch and the load, the non-linear characteristics of the tire cornering stiffness with load were obtained.

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.

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.

A procedure has been developed to build system level predictive models that incorporate physical laws as well as information derived from experimental data. In particular a soot model was developed, trained and tested using experimental data. It was seen that the model could fit available experimental data given sufficient training time. Future accuracy on data points not encountered during training was estimated and seen to be good. The approach relies on the physical phenomena predicted by an existing system level phenomenological soot model coupled with ‘weights’ which use experimental data to adjust the predicted physical sub-model parameters to fit the data. This approach has developed from attempts at incorporating physical phenomena into neural networks for predicting emissions. Model training uses neural network training concepts.

This paper describes the computational results of the flow field around two vehicle geometries using the Immersed Boundary (IB) technique in conjunction with a steady RANS CFD solver. The IB approach allows the computation of the flow around objects without requiring the grid lines to be aligned with the body surfaces. In the IB approach instead of specifying body boundary conditions, a body force is introduced in the governing equations to model the effect of the presence of an object on the flow. This approach reduces the time necessary for meshing and allows utilization of more efficient and fast CFD solvers. The simulations are carried out for an SUV and a pickup truck models at a Reynolds number of 8×105. Cartesian meshes (non-uniform) with local grid refinement are used to increase the resolution close to the boundaries. The simulation results are compared with the existing measurements in terms of surface pressures, velocity profiles, and drag coefficients.

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.