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Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

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.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

Driving safety is an eternal theme of the transportation industry. In recent years, with the rapid growth of car ownership, traffic accidents have become more frequent, and the harm it brings to human society has become increasingly serious. In this context, car safety assisted driving technology has received widespread attention. As an effective means to reduce traffic accidents and reduce accident losses, it has become the research frontier in the field of traffic engineering and represents the trend of future vehicle development. However, there are still many technical problems that need to be solved. With the continuous development of computer vision technology, face detection technology has become more and more mature, and applications have become more and more extensive. This article will use the face detection technology to detect the driver's face, and then analyze the changes in driver's driving focus.

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 working principle of dual mass flywheel - radial spring (DMF-RS) type torsional vibration damper was analyzed, and the design method of natural torsional vibration characteristics control of DMF-RS type torsional damper for automotive powertrains was studied herein. Based on the multi-freedom lumped mass - torsional vibration spring analysis model of powertrain, the natural torsional vibration characteristics of the system with DMF-RS type torsional damper were analyzed, and compared with the clutch type torsional vibration damper, the effectiveness of DMF-RS type torsional damper on the torsional vibration control was verified.

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.

Noise-vibration-harshness (NVH) design optimization problems have become major concerns in the vehicle product development process. The Body-in-White (BIW) plays an important role in determining the dynamic characteristics of vehicle system during the concept design phase. Finite Element (FE) models are commonly used for vehicle design. However, even though the speed of computers has been increased a lot, the simulation of FE models is still too time-consuming due to the increase in model complexity. For complex systems, like vehicle body structures, the numerous design variables and constraints make the FE simulations based optimization design inefficient. This calls for the development of a systematic and efficient approach that can effectively perform optimization to further improve the NVH performance, while satisfying the stringent design constraints.

Brake squeal is an instability issue with many parameters. This study attempts to assess the effect of thermal load on brake squeal behavior through finite element computation. The research can be divided into two parts. The first step is to analyze the thermal conditions of a brake assembly based on ANSYS Fluent. Modeling of transient temperature and thermal-structural analysis are then used in coupled thermal-mechanical analysis using complex eigenvalue methods in ANSYS Mechanical to determine the deformation and the stress established in both the disk and the pad. Thus, the influence of thermal load may be observed when using finite element methods for prediction of brake squeal propensity. A detailed finite element model of a commercial brake disc was developed and verified by experimental modal analysis and structure free-free modal analysis.

To obtain higher efficiency in analysis process, simplification methods for computer-aided engineering (CAE) models are required in engineering. Current model simplification methods can meet certain precision and efficiency requirement, but these methods mainly concentrate on model features while ignoring model mesh which is also critical to efficiency of the analysis process and preciseness of the results. To address such issues, an integrated mesh simplification and evaluation process is proposed in this paper. The mesh is simplified to fewer features (e.g. faces, edges, and vertices) through edge collapsing based on quadric error metric. Then curvatures and normal vectors which are the objects to be evaluated are extracted from the original and simplified models for comparison. To obtain accurate results, the geometric information of mesh nodes and elements are both considered in this evaluation process. The proposed method is implemented on a vehicle crash test.

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.

This paper presents a road classifier based on the system response with consideration of the tire enveloping. The aim is to provide an easily applicable yet accurate road classification approach for automotive engineers. For this purpose, tire enveloping effect is firstly modeled based on the flexible roller contact (FRC) theory, then transfer functions between road input and commonly used suspension responses i.e. the sprung mass acceleration, unsprung mass acceleration, and rattle space, are calculated for a quarter vehicle model. The influence of parameter variations, vehicle velocity, and measurement noise on transfer functions are comprehensively analyzed to derive the most suitable system response thereafter. In addition, this paper proposes a vehicle speed correction mechanism to further improve the classification accuracy under complex driving conditions.

In order to improve the comprehensive protection for children with variable shapes and sizes, this paper conducted studies on the impact injury for obese children based on a 10-YO finite element model. Some specific geometrics on the body surface were firstly acquired by the combination of pediatric anthropometric database and generator of body (GEBOD). A Radial Basis Function (RBF) based mesh morphing technique was then used to modify the original standard size FE model using the obtained geometrics. The morphed FE model was validated based on the experimental data of frontal sled test and chest-abdomen impact test. The effects of obesity on injury performances were analyzed through simplified high-speed and low-speed crash simulations.

China's auto market has developed rapidly in recent years and has become the world's largest auto market. The rapid increase in sales of passenger cars has brought a series of environmental and energy problems. In response to these problems, “The Parallel Management Method for Corporate Average Fuel Consumption and New Energy Vehicles Credits” (Dual-credit Regulation) has been enacted in 2018. However, some problems about the regulation were gradually exposed with the NEV subsidies decreasing, such as too much surplus new energy vehicle credit. To promote the development of NEV, the reform of dual credit regulation was issued in June,2020.

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.

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.

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.

Significant progress in modeling techniques has greatly enhanced the application of computer simulations in vehicle safety. However, the fine-meshed impact models are usually complex and take lots of computational resources and time to conduct design optimization. Hence, to develop effective methods to simplify the impact models without losing necessary accuracy is of significant meaning in vehicle crashworthiness analysis. Surface deformation is frequently regarded as a critical factor to be measured for validating the accuracy of CAE models. This paper proposes an integrated validation framework to evaluate the inconsistencies between the deformed surfaces of the original model and simplified model. The geometric features and curvature information of the deformed surfaces are firstly obtained from crash simulation. Then, the magnitude and shape discrepancy information are integrated into the validation framework as the surface comparison objects.

In real-world engineering problems, the method of model simplification is usually adopted to increase the simulation efficiency. Nevertheless, the obtained simulation results are commonly with low accuracy. To research the impact from model simplification on simulation results, a feature-based predictive method for simplified CAE model analysis is proposed in this paper. First, the point clouds are used to represent the features of simplified model. Then the features are quantified according to the factors of position for further analysis. A formulated predictive model is then established to evaluate the responses of interest for different models, which are specified by the employed simplification methods. The proposed method is demonstrated through an engineering case. The results suggest that the predictive model can facilitate the analysis procedure to reduce the cost in CAE analysis.