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Chopped carbon fiber sheet molding compound (SMC) material is a promising material for mass-production lightweight vehicle components. However, the experimental characterization of SMC material property is a challenging task and needs to be further investigated. There now exist two ASTM standards (ASTM D7078/D7078M and ASTM D5379/D5379M) for characterizing the shear properties of composite materials. However, it is still not clear which standard is more suitable for SMC material characterization. In this work, a comparative study is conducted by performing two independent Digital Image Correlation (DIC) shear tests following the two standards, respectively. The results show that ASTM D5379/D5379M is not appropriate for testing SMC materials. Moreover, the failure mode of these samples indicates that the failure is caused by the additional moment raised by the improper design of the fixture.

To advance vehicle lightweighting, chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, a Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed to populate the RVE. The elastic moduli of the RVE are calculated and the two methods are compared with experimental tensile test conduct using Digital Image Correlation (DIC). Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.

The dynamic trajectory planning problem for automatic vehicles in complex traffic scenarios is investigated in this paper. A hierarchical motion planning framework is developed to complete the complex planning task. An improved dangerous potential field in the curvilinear coordinate system is constructed to describe the collision risk of automatic vehicles accurately instead of the discrete Gaussian convolution algorithm. At the same time, the driving comfort is also considered in order to generate an optimal, smooth, collision-free and feasible path in dynamics. The optimal path can be mapped into the Cartesian coordinate system simply and conveniently. Furthermore, a velocity profile considering practical vehicle dynamics is also presented to improve the safety and the comfort in driving. The effectiveness of the proposed dynamic trajectory planning is verified by numerical simulation for several typical traffic scenarios.

High fidelity mathematical vehicle models that can accurately capture the dynamics of car suspension system are critical in vehicle dynamics studies. System identification techniques can be employed to determine model type, order and parameters. Such techniques are well developed and usually used on linear models. Unfortunately, shock absorbers have nonlinear characteristics that are non-negligible, especially with regard the vehicle's vertical dynamics. In order to effectively employ system identification techniques on a vehicle, a nonlinear mathematical shock absorber model must be developed and then coupled to the linear vehicle model. Such an approach addresses the nonlinear nature of the shock absorber for system identification purposes. This paper presents an approach to integrate the nonlinear shock absorber model into the vehicle model for system identification.

The study of vehicle coupling state estimation accuracy especially in observer-based vehicle chassis control for improving road handling and ride comfort is a challenging task for vehicle industry under various driving conditions. Due to a large amount of life safety arising from vehicle roll behavior, how to precisely acquire vehicle roll state and rapidly provide for the vehicle control system are of great concern. Simultaneously, uncertainty is unavoidable for various aspects of a vehicle system, e.g., varying sprung mass, moment of inertia and position of the center of gravity. To deal with the above issues, a novel dual observer approach, which combines adaptive Unscented Kalman Filter (AUKF) and Takagi-Sugeno (T-S), is proposed in this paper. A full-car nonlinear model is first established to describe vehicle lateral and vertical coupling roll behavior under various road excitation.

This paper proposed a two-section trajectory planning algorithm. In this trajectory planning, sigmoid function is adopted to fit two tangent arcs to meet limited parking spaces by reducing the radius of turning. Then the transverse preview model is established and the path tracking errors including distance error and angle error are estimated. The weight coefficient is considered to distribute the impact factor of traverse distance error or traverse angle error in the total error. The fuzzy controller is designed to track the two-section trajectory in autonomous intelligent parking system. The fuzzy controller is developed due to its real-time and robustness in the parking process. Traverse errors and its first-order derivative are selected as input variables and the outer wheel steering angle is selected as the output variable in fuzzy controller. They are also divided into seven fuzzy sets. Finally, forty rules are decided to achieve effective trajectory tracking.

This paper describes a uniform Hardware-In-the-Loop (HiL) test rig for the different types of Electronic Braking System (EBS). It is applied to both modular testing and integrated testing. This test rig includes a vehicle dynamic model, a real-time simulation platform, an actual brake circuit and the EBS system under test. Firstly, the vehicle dynamic model is a highly parameterized commercial vehicle model. So it can simulate different types of commercial vehicle by different parameter configurations. Secondly, multi-types of brake circuit are modeled using brake components simulation library. So, it can test the EBS control unit independently without the influence of any real electro-pneumatic components. And a software EBS controller is also modeled. So it can test the algorithm of EBS offline. Thirdly, all real electro-pneumatic components without real gas inputted are connected to the real-time test platform through independent program-controlled relay-switches.

This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.

According to driving scenarios, intelligent vehicle is mainly applied on urban driving, highway driving and close zone driving, etc. As one of the most valuable developments, automated highway driving has great progress. This paper focuses on automated highway driving decision, and considering decision efficiency and feasibility, a hierarchical motion planning algorithm based on dynamic programming was proposed, and simultaneously, road coordinate transformation methods were developed to deal with complex road conditions. At first, all transportation user states are transformed into straight road coordinate to simplify modeling and planning, then a set of candidate paths with Bezier form was developed and with the help of obstacles motion prediction, the feasible target paths with collision-free were remains, and via comparing vehicle performance for feasible path, the optimal driving trajectory was generated.

ADAS must be tested thoroughly before they can be deployed for series production. Comparing with road and field test, bench test has been widely used owing to its advantages of less labor costs, more controllable scenarios, etc. However, there is no satisfied systematic approach to generate high-efficiency and full-coverage test scenarios automatically because of its integration of human, vehicle and traffic. Most of the test scenarios generated by the existing methods are either too simple or too few to be able to achieve full coverage of requirements. Besides, the cost is high when the ET method is used. To solve the aforementioned problems, an automatic test scenario generation method based on complexity for bench test is presented in this paper. Firstly, considering the fact that the device is easier to malfunction under complex cases, an index measuring the complexity of test case is proposed by using the method of AHP.

The control parameter of the semi-active suspension system varies with road profile; therefore, in this study a new algorithm based on cuckoo search (CS) optimization method and road estimation was proposed to investigate the characteristics of the nonlinear parameters and at the same time improve the riding comfort. Based on this, a seven degree of freedom full vehicle model was developed with nonlinear damper and spring. The sprung mass acceleration, pitch acceleration, and tire deflection could be selected as the objective functions, and the control current of semi active suspension was selected as optimization variable. A multi-object CS algorithm was utilized to obtain the optimal parameters under different road profiles, and a road estimation algorithm was used to identify the road level. Then the control parameters could be adjusted adaptively according to the level of the road.

This paper presents a new method which adopts the theory of multi-rigid body system dynamics to solve the kinematics of multi-axle steering system of heavy-duty vehicle, introduces several new concepts such as component coordinate system, intermediate datum coordinate system, train component analysis method, and so on, develops a kinematics analysis software for steering system, takes QY80 auto-crane as an example, analyses the kinematics of four-axle steering system. Basing on the kinematics analysis, this paper creates the mathematical model of optimization for the steering rocker mechanism, chooses minimization adoptive random search method to develop an optimization design microcomputer program, and optimizes each design variable finally.

The paper presents the design and analysis of pure electric bus powered by Lithium-ion battery and ultra capacitor. For the limited power energy of battery, the ultra capacitor pack is chosen as the auxiliary on-board energy storage device. The system configuration, system modeling and on-road test result analysis will be covered in the paper and the possibility of using ultra capacitors on electric bus to improve the economical efficiency in urban areas will be discussed.

In this paper the hardware and software of a real-time dynamic test bench for simulating the total road forces of vehicles fitted with Automated Manual Transmissions (AMT) is described. First, the purpose and meaning of this research are discussed. And then, we select the hardware components of the test bench system according to the application requirements and complete the system design. Statement of the structure, working principle and function of the system is also included in this part. According to the experimental procedure of simulating total road load forces of vehicle under real-time conditions on the dynamic test bench, the software system is designed using Visual C++ 6.0, CAN bus communication protocol, RS-232, and network technology. Finally, some experimental tests for the system are carried out with the results that this design corresponds to the real-time dynamic requirements.

The electric vehicles and the intelligent vehicles put forward to new requirements for the brake system, such as the vacuum-independent braking, automatic or active braking, and regenerative braking, which are the key link for the vehicle’s safety and economy. However, the traditional vacuum brake booster is no longer able to meet these requirements. In this article, a novel integrated power-assisted actuator of brake system is proposed to satisfy the brake system requirements of the electric vehicles and intelligent vehicles. The electronic brake booster system is designed to achieve the function of boosting pedal force of driver, being independent on vacuum source, supplying autonomous or active braking. It is mainly composed of a permanent magnet synchronous motor (PMSM), a two-stage reduction transmission (gears and a ball screw), a servo body, and a reaction disk. The scheme design and power-assisted braking control are the key for the electronic actuator.

The high strength-weight ratio and high damping capability of Magnesium alloys implies significant potentials for improving fuel efficiency and vehicle performance with the use Mg wheels. In this paper, a brief review is given of the current state of art in Mg wheel production, followed by a summary of the mechanical and casting properties of Mg alloys. The difficulties that hinder the wide use of Mg wheels are discussed. The R&D activities in China in the fields of Mg wheel design and casting are described. The focus of this paper is on the design and the development of a new squeeze casting process that makes it feasible to produce high-quality Mg wheels with cost efficiency. Finally, the expected commercial use of Mg wheels in the near future in Chinese motorbikes is outlined.

The study of mechanical properties special in the characteristics of elastic element is a challenging task for vehicle industry. Since torsion bar spring acts as an important part of elastic element, and improves performance of torsion bar spring is of great concern. The effects of the torsion bar spring pre-setting precision on the presetting performance are presented. Based on elastic-plastic theories, the algebraic model of torsion bar spring is established to analyze the stress, torque and residual stress under the yield and plastic conditions in pre-setting process. Then, the stress and strain states of various torsion bar springs in different conditions are simulated using the validated finite element model in ABAQUS software. The simulation results show the effects of torsion error on the pre-setting performance are less than 5% in the pre-setting process.

The study of vehicle state estimation performance especially on the aspect of observer-based control for improving vehicle ride comfort and road handling is a challenging task for vehicle industry. Since vehicle roll behavior with various road excitations act an important part of driving safety, how to accurately obtain vehicle state under various driving scenes are of great concern. However, previous researches seldom consider coupling relation between vehicle vertical and lateral response with steering input under various road excitation. To address this issue, comprehension analyses on vehicle roll state estimation with coupled input are present in this paper. A full-car nonlinear Takagi-Sugeno (T-S) fuzzy model is first created to describe vehicle lateral and vertical coupling dynamics.

Due to traffic congestion and environmental pollution, connected automated vehicle (CAV) technologies based on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communication (V2I) have gained increasing attention from both academia and industry. Connected hybrid electric vehicles (CHEVs) offer great opportunities to reduce vehicular operating costs and emissions. However, in complex traffic scenarios, high-quality real-time energy management of CHEVs remains a technical challenge. To address the challenge, this paper proposes a hierarchical eco-driving strategy that consists of speed planning and energy management layers. At the upper layer, by leveraging the real-time traffic data provided by vehicle-to-everything (V2X) communication, dynamic traffic constraints are predicted by the traffic flow predictor developed based on the Hankel dynamic mode decomposition algorithm (H-DMD).

In this paper, a closed loop path planning and tracking control approach of collision avoidance for autonomous vehicle is proposed. The two-level model predictive control (MPC) is proposed for the path planning and tracking. The upper-level MPC is designed based on the simple vehicle kinematic model to calculate the collision-free trajectory and the potential field method is adopted to evaluate the collision risk and generate the cost function of the optimization problem. The lower-level MPC is the trajectory-tracking controller based on the vehicle dynamics model that calculates the desired control inputs. Finally the control inputs are distributed to steering wheel angle and motor torque via optimal control vectoring algorithm. Test cases are established on the Simulink/CarSim platform to evaluate the performance of the controller.