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Direct debugging of a vertical takeoff and landing (VTOL) fixed-wing aircraft’s control system can easily result in risk and personnel damage. It is effectively to employ simulation and numerical methods to validate control performance. In this paper, the attitude stabilization controller for VTOL fixed-wing aircraft is designed, and the controller performance is verified by MATLAB and visual simulation software, which significantly increases designed efficiency and safety of the controller. In detail, we first develop the VTOL fixed-wing aircraft’s six degrees of freedom kinematics and dynamics models using Simulink module, and the cascade PID control technique is applied to the VTOL aircraft’s attitude stabilization control. Then the visual simulation program records the flight data and displays the flight course and condition, which can validate the designed controller performance effectively.

In this paper, the MDO analysis is applied to the design integration in terms of NVH and crash safety. Considering the difference of characteristics in these two fields, all the design variables are used to construct the response surfaces in the NVH analysis, while for crash safety analysis, these design variables are split into three groups, front, side and rear, to reduce the computational cost. Many of the structure performance indices in the NVH and crash safety fields are included as the constraints in the MDO analysis, which proves that the design integration of these two fields through MDO analysis is feasible. A comparison of crash safety optimization and crash safety-NVH MDO is done through a parallel-coordinate diagram. The difference provides the CAE engineers to find the guidance to modify the original design architecture.

Due to the individual controllability of each motor, the distributed driven electric vehicle has provided a broad research domain for vehicle integrated control. This paper focuses on vehicle stability control by the integration of three systems, the hydraulic brake unit, active steering unit, and motor torque control unit. Firstly, the hierarchical control strategy has been designed generally, which is divided into three levels, the upper controller, medium controller, and lower controller. Secondly, based on the hierarchical structure, each controller has been introduced in detail. The upper controller is the application layer, which has implemented the functions such as the estimations of vehicle states and road conditions, calculation of nominal control variables, identification of vehicle stability and steering characteristics, and the coordinated algorithm of additional yaw moment and active front angle, etc.

The around view monitor (AVM) system for vehicles usually suffers from the distortion of surrounding objects caused by incomplete rectification and stitching, which seriously affects the driver's judgment of the surrounding environment during the reversing process. In response to solve this problem, an augmented around view monitor (AAVM) system fusing image and depth information is proposed, which highlights the point clouds of persons or vehicles at the rear of the vehicle. First, an around view image is generated from four fisheye cameras. Then, the calibration of multi TOF cameras is conducted to improve their accuracy of depth estimation and obtain extrinsic camera positions. Next, the 2D-driven object point cloud detection method is proposed to localize and segment object point clouds like vehicles or persons.

The drivability plays an important role for marketability and competitiveness of passenger car in meeting some customer requirements, which directly affects the driving experience and the desire of purchasing. In this paper, a framework of objective drivability evaluation with multi-source information fusion for passenger car is proposed. At first, according to vehicle powertrain system and optimization theory, certain vehicle performances, which are closely related to objective drivability are analyzed, including vehicle longitudinal acceleration, vehicle speed, engine torque, engine speed, gear position, accelerator pedal, brake signal and voltage signal. Then, combined with the evaluation criterion of signal-to-noise ratio (SNR), mean error (ME), root mean squared error (RMSE) and signal smoothness (SS), a de-noising method is developed for the drivability evaluation information.

BOBC (Bi-directional on-board charger) is a power conversion system component for AC charging and discharging of new energy vehicles. It has two working modes: AC charging mode and AC discharge mode. In the two working modes, the BOBC belongs to both the controller and the actuator. In some extreme cases such as communication and control failure of the AC charging mode, new energy vehicles have the risk of high-voltage battery overcharging and overheating, which will lead to high-voltage battery fire or even explosion. In the AC discharge mode, it involves the actual operation of the users on electricity, and the risk of short circuit and open circuit may happen in the process, which endangers the safety of the users. Based on the risks brought by the two working modes, it should pay more attention to the safety of the BOBC.

The hydraulic retarder used in commercial vehicles can provide hydraulic damping to generate braking torque, reducing the pressure of the braking system on the slope section and increasing the safety. In this paper, the magnetorheological fluid with fast magnetic field reflection characteristics is used to increase the response speed of the hydraulic retarder, which can effectively reduce the response time of the hydraulic retarder. In this paper, the influence of the change of circumferential magnetic field on the braking torque of the magnetorheological fluid retarder is studied.

The around view monitor (AVM) system for the long-body road vehicle with multiple articulated carriages usually suffers from the incomplete distortion rectification of fisheye cameras and the irregular image stitching area caused by the change of relative position of the cameras on different carriages while the vehicle is in motion. In response to these problems, a set of calibration and stitching methods of AVM are proposed. First, a radial-distortion-based rectification method is adopted and improved. This method establishes two lost functions and solves the model parameters with the two-step optimization method. Then, AVM system calibration is conducted, and the perspective transformation matrix is calculated. After that, a static basic look-up table is generated based on the distortion rectification model and perspective transformation matrix.

Path tracking is one of the critical technologies in the autonomous vehicle. Its performance may be seriously affected by disturbance resulting from unpredictable environment like changes in road friction coefficient and parameter uncertainty such as cornering stiffness and mass caused by errors of measurement. Besides, since the vehicle system consisting of many systems is an extremely complex nonlinear system, it is almost impossible for us to establish a precise model of a vehicle especially when it is moving. These inevitable factors influence the control accuracy and even threaten the stability and safety of the vehicle system. This paper proposed a promising solution to this problem, robust MPC (Model Predictive Control) combined with the optimal preview controller for path tracking problems of an autonomous vehicle. The state space model in tracking error variables of a passenger vehicle used for path tracking application is established.

In order to perform differential control instead of the mechanical differential and improve the steering performance of distributed electric vehicles, a two-level differential speed steering control strategy is proposed. Firstly, an upper-layer controller to track the yaw rate is designed based on PID feedback and 3-D lookup table model, which could shorten the response time and reduce the impact of model parameters mismatch. Then, in order to improve the robustness to external disturbances and parameter uncertainties, a lower-layer controller to track the wheel speed is proposed based on integral sliding mode control. Moreover, three simulations are conducted to validate the proposed strategy. The first simulation results indicate that the driving torques of the inner and outer wheels are distributed properly to avoid wheel slip. In the second simulation, when the conventional steering system fails, the proposed control strategy could avoid vehicle losing steering function.

The current paper proposes a hydraulic interconnected suspension system (HIS) based on a hydraulic energy-regenerative shock absorber (HESA) comparatively with the passive suspensions. The structure and working principles of the HIS system are introduced in order to investigate the damping performance and energy regeneration characteristics of the proposed system. Then, the dynamic characteristics of the HIS-HESA system have been investigated based on a 4-DOF longitudinal half vehicle model. In the simulation, two different road inputs were used in the dynamic characterization of the HIS-HESA; the warp sinusoidal excitation, and the random road signal. In addition, a comparative analysis was provided for the dynamic responses of the half vehicle model for both the HIS-HESA and the conventional suspension. Furthermore, a parametric analysis of the HIS-HESA has been carried out highlining the key parameters that have a remarkable effect on the HIS-HESA performance.

In recent years, more attentions have been paid to stringent legislations on fuel consumption and emissions. Turbocharged downsized gasoline direct injection (DI) engines are playing an increasing important role in OEM’s powertrain strategies and engine product portfolio. Dongfeng Motor (DFM) has developed a new 1.0 liter 3-cylinder Turbocharged gasoline DI (TGDI) engine (hereinafter referred to as C10TD) to meet the requirements of China 4th stage fuel consumption regulations and the China 6 emission standards. In this paper, the concept of the C10TD engine is explained to meet the powerful performance (torque 190Nm/1500-4500rpm and power 95kW/5500rpm), excellent part-load BSFC and NVH targets to ensure the drivers could enjoy the powerful output in quiet and comfortable environment without concerns about the fuel cost and pollution.

After obtaining the optimal trajectory through the lane change decision and trajectory planning, the last key technology for the automatic lane change assist system is to carry out the precise and rapid steering actuation according to the front wheel angle demand. Therefore, an automatic lane change system model including a BLDCM (brushless DC motor) model, a steering system model and a vehicle dynamics model is first established in this paper. Electromagnetic characteristics of the motor, the moment of the inertia and viscous friction etc. are considered in these models. Then, a SMC (Sliding Mode Control) algorithm for the steering system is designed to follow the steering angle input. The control torque of the steering motor is obtained through the system model according to steering angle demand. After that, the control current is calculated considering of electromagnetic characteristics of the BLDCM. Debugging and optimization of the control algorithm are done through simulations.

Dynamic modeling and state estimation are significant in the trajectory tracking and stability control of the intelligent vehicle. In order to meet the requirement of the stability control of the eight-in-wheel-motor-driven intelligent vehicle, a full vehicle dynamics model with 12 degrees of freedom, including the longitudinal, lateral, yaw and roll motion of the body, and rotational motion of 8 wheels, is established for the research of the intelligent vehicle in this paper. By simulation with MATLAB/SIMULINK and by comparison with the TruckSim software, the reliability and practicality of the dynamics model are verified. Based on the established dynamics model, an extended Kalman filter (EKF) state observer is proposed to estimate the vehicle sideslip angle, roll angle and yaw rate, which are the key parameters to the stability control of the intelligent vehicle.

The automatic lane change assist system is an intelligent driving assistance technology oriented to traffic safety, which requires trajectory planning of the lane change maneuver based on the lane change decision. A typical scene of lane change for overtaking is selected, where the front vehicle in the same lane and the rear vehicle in the left lane are deemed to be potential dangerous vehicles through the lane change. Lane change trajectory equation is first established according to the general law of steering wheel angle through lane changes. Based on the relative position, velocity and acceleration information of the dangerous vehicles and the lane change vehicle, motions of these surrounding dangerous vehicles are predicted. At the same time, a multi-objective optimization function is established based on the relative longitudinal safety boundary. The objectives are the minimum safety distance, the lane change time and the front wheel angle.

Automotive Front Lighting System(AFS) can receive the steering signal and the vehicular speed signal to adjust the position of headlamps automatically. AFS will provide drivers more information of front road to protect drivers safe when driving at night. AFS works when there is a steering signal input. However, drivers often need the front road's information before they turn the steering wheel when vehicles are going to go through a sharp corner, AFS will not work in such a situation. This paper studied how to optimize the working time of AFS based on GIS (Geographic Information System) and GPS(Geographic Information System) to solve the problem. This paper analyzed the process of the vehicle is about to go through a corner. Low beams and high beams were discussed respectively.

Brake pedal feel plays an important role in the driver's comprehensive subjective feeling when braking, which directly affects the active safety and riding comfort of passenger car. A systematical mathematical model of the vehicle brake system is built in according with the structure and system characteristics of hydraulic servo brake system. A complete hydraulic servo brake system simulation model composed of brake pedal, vacuum booster, brake master cylinder, brake pipe, brake wheel cylinders, brake calipers is established in AMESim. The effects of rubber reaction plate stiffness, rubber valve opening, brake master cylinder piston, brake caliper, brake pipe deformation and friction liner deformation on brake pedal feel are considered in this model. The accuracy of this model is verified by real road vehicle tests under static and dynamic two different conditions.

Path planning system, which is one of driver assistance systems, can calculate the driving paths and estimate the driving time through the road information provided by information source. Traditional path planning systems calculate the driving paths through Dijsktra's algorithm or A* algorithm but only consider the road information from electronic maps. It is not safe enough for operating vehicles because of the insufficient information of vehicle performance as well as the driver's willingness. This study is based on the Dijsktra's algorithm, which comprehensively considered vehicular active safety constraints such as road information, vehicle performance and the driver's willingness to optimize the Dijsktra's algorithm. Then the path planning system can calculate the optimal driving paths that would satisfy the safety requirement of the vehicle. This study used LabVIEW as a visual host computer and MATLAB to calculate dynamic property of the vehicle.

In this paper a new pressure control method of a modified accumulator-type Electro-hydraulic Braking System (EHB) is proposed. The system is composed of a hydraulic motor pump, an accumulator, an integrated master cylinder, a pedal feel simulator, valves and pipelines. Two pressurizing modes are switched between by-motor and by-accumulator to adapt different pressure boost demands. A differentiator filtering raw sensor signal and calculating pedal speed is designed. By using the pedal feel simulator, the relationship between wheel pressures and brake force is decoupled. The relationships among pedal displacement, pedal force and wheel pressure are calibrated by experiments. A model-based PI controller with predictor is designed to lower the influences caused by delay. Moreover, a self-tuning regulator is introduced to deal with the parameter’s time-varying caused by temperature, brake pads wearing and delay variation.

Vehicle hydraulic retarders are applied in heavy-duty trucks and buses as an auxiliary braking device. In traditional cooling systems of hydraulic retarders, the working fluid is introduced into the heat exchanger to transfer heat to the cooling liquid in circulation, whose heat is then dissipated by the engine cooling system. This prevents the waste heat of the working fluid from being used effectively. In hydraulic retarder cooling system based on the Organic Rankine Cycle, the organic working fluid first transfers heat with the hydraulic retarder working fluid in Rankine cycle, and then outputs power through expansion machine. It can both reduce heat load of the engine cooling system, and enhance thermal stability of the hydraulic retarder while recovering and utilizing braking energy. First of all, according to the target vehicle model, hydraulic retarder cooling system model based on Rankine cycle is established.