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The Electronic Mechanical Braking (EMB) system, which offers advantages such as no liquid medium and complete decoupling, can meet the high-quality active braking and high-intensity regenerative braking demands proposed by intelligent vehicles and is considered one of the ideal platforms for future chassis. However, traditional control strategies with fixed clamping force tracking parameters struggle to maintain high-quality braking performance of EMB under variable braking requests, and the nonlinear friction between mechanical components also affects the accuracy of clamping force control. Therefore, this paper presents an adaptive clamping force control strategy for the EMB system, taking into account the resistance of nonlinear friction. First, an EMB model is established as the simulation and control object, which includes the motor model, transmission model, torque balance model, stiffness model, and friction model.

The accuracy of tire forces directly affects the vehicle dynamics model precision and determines the ability of the model to develop the simulation platform or design the control strategy. In the high slip angle, due to the complex interactions at tire-road interfaces, the forces generated by the tires are high nonlinearity and uncertainty, which pose issues in calculating tire force accurately. This paper presents a hybrid physical and data-driven tire force calculation framework, which can satisfy the high nonlinearity and uncertainty condition, improve the model accuracy and effectively leverage prior knowledge of physical laws. The parameter identification for the physical tire model and the data-based compensation for the unknown errors between the physical tire model and actual tire force data are contained in this framework. First, the parameters in the selected combined-slip Burckhardt tire model are identified by the nonlinear least square method with tire test data.

Accurate sensing of road conditions is one of the necessary technologies for safe driving of intelligent vehicles. Compared with the structured road, the unstructured road has complex road conditions, and the response characteristics of vehicles under different road conditions are also different. Therefore, accurately identifying the road categories in front of the vehicle in advance can effectively help the intelligent vehicle timely adjust relevant control strategies for different road conditions and improve the driving comfort and safety of the vehicle. However, traditional road identification methods based on vehicle kinematics or dynamics are difficult to accurately identify the road conditions ahead of the vehicle in advance. Therefore, this paper proposes an unstructured road region detection and road classification algorithm based on machine vision to obtain the road conditions ahead.

The hippocampus plays a crucial role in brain function and is one of the important areas of concern in closed head injury. Hippocampal injury is related to a variety of factors including the strength of mechanical load, animal age, and helmet material. To investigate the order of these factors on hippocampal injury, a three-factor, three-level experimental protocol was established using the L9(34) orthogonal table. A closed head injury experiment regarding impact strength (0.3MPa, 0.5MPa, 0.7MPa), rat age (eight- week-old, ten-week-old, twelve-week-old), and helmet material (steel, plastic, rubber) were achieved by striking the rat's head with a pneumatic-driven impactor. The number of hippocampal CA3 cells was used as an evaluation indicator. The contribution of factors to the indicators and the confidence level were obtained by analysis of variance.

With the increasingly complex traffic environment, the vehicle AEB system needs to go through a large number of testing processes, in order to drive more safely on the road. For speeding up the development process of AEB and solve the problems of long cycle, high cost and low efficiency in AEB testing, in this paper, a millimeter wave radar turntable is built, and a high-precision detection algorithm of turntable encoder is designed, at the same time, a test method of vehicle AEB based on the detection data of radar turntable encoder is designed. The verification results show that methods described in this paper can be used to develop the vehicle AEB test algorithm efficiently.

The Electromechanical Brake Booster system (EMBB) integrates active braking and energy recovery and becomes a novel brake-by-wire solution that substitutes the vacuum booster. While the intelligent unmanned vehicle is in unstable state, the EMBB can improve the vehicle yaw stability more quickly and safely. In this paper, a new type of integrated EMBB has been designed, which mainly includes two parts: servo motor unit and hydraulic control unit. Aiming at the dynamic instability problem of intelligent unmanned vehicle, a three-layer vehicle yaw stability control structure including decision layer, distribution layer and execution layer is proposed based on integrated EMBB. Firstly, the decision layer calculates the ideal yaw rate and the side slip angle of the vehicle with the classic 2DOF vehicle dynamics model. The boundary of the stable region is determined by the phase plane method and the additional yaw moment is determined by the feedback PI control algorithm.

A high-precision steady state tire model is critical in the tire and vehicle matching research. For the moment, the popular Magic Formula model is an empirical model, which requires the pure and combined test data to identify the model parameters. Although MTS Flat-trac is an efficient tire test rig, the long test period and high test cost of a complete tire model tests for handling are yet to be solved. Therefore, it is necessary to explore a high accuracy method for predicting tire complex mechanical properties with as few test data as possible. In this study, a method for predicting tire combined slip characteristics from pure cornering and pure longitudinal test data has been investigated, and verified by comparing with the test data. Firstly, the prediction theory of UniTire model is introduced, and the formula for predicting combined slip characteristics based on constant friction coefficient is derived.

With the prevalent trend of the pure electric vehicle, vehicle interior noise has been reduced significantly. However, other noises become prominent in the cabin. Especially, the BSR noise generated by friction between parts and the clearance between components become the elements of complaints directly affect the quality of vehicles. Currently, the BSR noises are subjectively evaluated by experts, and the noise samples are simply labeled as ‘qualified’ or ‘unqualified’. Therefore, it is necessary to develop an evaluation model to assess the BSR noise objectively. In this paper, we study the vehicle rattle noise intensively. Several types of rattle noise were recorded in a semi-anechoic room. The recorded signals were then processed in the LMS test lab. to extract the single impact segments. A pool of simulated signals with different impact rates (number of impacts per second) and various loudness was synthesized for analyzation.

The requirement for low emissions and better vehicle performance has led to the demand for lightweight vehicle structures. Two new lightweight methods of design and optimization for the lower control arm were proposed in this research to improve the effectiveness of the traditional lightweight method. Prior to the two lightweight design and optimization methods, the static performance, including strength, stiffness and mode, and fatigue performance for the lower control arm were analyzed and they provided constraints for subsequent design and optimization. The first method of lightweight design and optimization was integrated application of topography optimization, size optimization, shape optimization and free shape optimization for the control arm. Topography optimization was first applied to find the optimal distribution form of reinforcement rib for the lower control arm. Size optimization was then applied in this study to optimize the plate thickness.

A vehicle’s NVH performance has a significant impact on the user experience of the driver and passengers. About one-third of the vehicle complaints are related to NVH performance. As the core component of the vehicle, the drivetrain’s NVH characteristics have a significant impact on vehicle comfort. How to reliably and stably reproduce the specific condition of the whole vehicle through the test method, and obtain the highly consistent objective data for analyzing and improving the NVH characteristics of the drivetrain is of great significance in engineering. For this purpose, China Automotive Technology Research Center Co., Ltd. (CATARC) designed and built a new type drivetrain NVH test facility, which consists of five dynamometers, and can carry horizontal/vertical, front/rear drive or four-wheel drive structures including powertrain, transmission, and rear axle, or even a whole vehicle.

As a critical part of auto-body, the design of tailgate not only affects the beauty, usability and safety of automobile, but also involves more and more issues about environmental protection and energy saving. Hence, it is of vital importance to investigate lightweight of tailgate. This paper mainly focuses on lightweight design of CFRP tailgate based on conventional SUV metal tailgate, which can be realized under the condition of meeting requirements of stiffness, modal and manufacturing with the adoption of multi-step optimization method. To start with, finite element (FE) model of metal tailgate is established. Meanwhile, the stiffness and modal analyses, including bending stiffness, torsional stiffness, lateral stiffness, vertical stiffness and free modal are set up. Then, the structural performances of metal tailgate are analyzed, and the topology optimization of CFRP tailgate is performed.

In this paper, it was researched the degradation characteristics of catalytic performance of three kinds of DPFs (C1, C2 and C3, with precious metal concentrations being 15, 25 and 35 g/ft3 respectively) after diesel truck aging. It is found out that the crystallinity of three kinds of DPF samples (Used) in full vehicle aging was higher than that of fresh samples (Fresh) and aged samples (Aged) in the laboratory. Compared with Fresh samples, the concentration of Pt atom in precious metal on the surface of Aged and Used samples tends to decrease in most cases. Activities to CO and C3H8 of Aged and Used samples of three kinds of DPFs had all been degraded, and activity degradation showed a substantial correlation with concentration reduction rate of precious metal on the carrier surface. NO2 productivity of Used samples all rose. Crystallinity of DPF samples after full vehicle aging in Inlet, Middle and Outlet areas successively increased.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

It aims to study the unsteady flow characteristic of the side-view mirror wake field, and reduce the wind noise by means of unsteady flow control. In this paper, the PIV test in a wind tunnel is used to capture the unsteady flow in the wake field of the side-view mirror, which is used to verify the accuracy of the steady simulation method with RANS after being averaged. Then LES turbulence model is used to obtain the wind noise, and the unsteady flow characteristic like vortex shedding of the side-view mirror is studied. The results show that, in the wake of the side-view mirror, there is a vortex pair similar to Karman Vortex Street. In both horizontal and vertical sections, these two vortexes are respectively separated from the upper and lower edges of the side-view mirror. Accompanied by a significantly uncertain periodic shedding, they continue to extend back until dissipating.

This paper presents the feasibility study of using the worldwide harmonized light vehicles test cycle (WLTC) for the fuel consumption certification of Chinese Light-duty (LD) vehicles. First, the key steps and the technical routes of the development process of WLTC are summarized. Second, the operation data of 3082 vehicles in 41 typical cities of China are collected throughout the year. Then, the characteristics of the acquisition data are compared with WLTC. Finally, the feasibility of using WLTC for fuel consumption certification of Chinese LD vehicles is analyzed in three aspects, includes operation characteristics, weighting factors and fuel consumption. The result shows that there is obvious difference between WLTC and Chinese reality, and WLTC is not suitable for the fuel consumption certification of Chinese LD vehicles.

Most of the Advanced Driver Assistance System (ADAS) applications are aiming at improving both driving safety and comfort. Understanding human drivers' driving styles that make the systems more human-like or personalized for ADAS is the key to improve the system performance, in particular, the acceptance and adaption of ADAS to human drivers. The research presented in this paper focuses on the classification and identification for personalized driving styles. To motivate and reflect the information of different driving styles at the most extent, two sets, which consist of six kinds of stimuli with stochastic disturbance for the leading vehicles are created on a real-time Driver-In-the-Loop Intelligent Simulation Platform (DILISP) with PanoSim-RT®, dSPACE® and DEWETRON® and field test with both RT3000 family and RT-Range respectively.

The conventional hood with single material and stiffener structural form conceals some limitations on pedestrian protection and lightweight, not satisfying the requirements of structural strength, pedestrian protection and lightweight contradictory with each other at the same time. In this paper, a novel type hood is proposed to develop sandwich structure using architected cellular material with negative Poisson's ratio (NPR) configuration based on the decoupling thought of structural strength and energy absorption. Core-layer aluminum alloy material with NPR is used to meet the requirement of impact energy absorption, inner and outer skin using carbon fiber is selected to achieve high structural stiffness needed. This paper starts from the relations between geometric parameters of core-layer architected cellular material and mechanical properties, on this basis, the optimal geometric parameters can be expected using the multiobjective optimization method.

This study presents a hybrid optimization approach of TOPSIS-based Taguchi method and entropy measurement for the determination of the optimal suspension parameters to achieve an enhanced compromise among ride comfort, road friendliness which means the extent of damage exerted on the road by the vehicles, and handling stabilities of a self-dumping truck. Firstly, the full multi-body dynamic vehicle model is developed using software ADAMS/Car and the vehicle model is then validated through ride comfort road tests. The performance criterion for ride comfort evaluation is identified as root mean square (RMS) value of frequency weighted acceleration of cab floor, while the road damage coefficient is used for the evaluation of the road-friendliness of a whole vehicle. The lateral acceleration and roll angle of cab were defined as evaluation indices for handling stability performance.

In this paper, the performance simulation model of a domestic self-dumping truck was established using AVL-Cruise software. Then its accuracy was checked by the power performance and fuel economy tests which were conducted on the proving ground. The power performance of the self-dumping truck was evaluated through standing start acceleration time from 0 to 70km/h, overtaking acceleration time from 60 to 70km/h, maximum speed and maximum gradeability, while the composite fuel consumption per hundred kilometers was taken as an evaluation index of fuel economy. A L9 orthogonal array was applied to investigate the effect of three matching factors including engine, transmission and final drive, which were considered at three levels, on the power performance and fuel economy of the self-dumping truck. Furthermore, the grey relational grade was proposed to assess the multiple performance responses according to the grey relational analysis.

In this paper, the dynamic stress of the front subframe of a passenger car was obtained using modal stress recovery method to estimate the fatigue life. A finite element model of the subframe was created and its accuracy was checked by modal test in a free hanging state. Furthermore, the whole vehicle rigid-flexible coupling model of the passenger car was built up while taking into account the flexibility of the subframe. Meanwhile, the road test data was used to verify the validity of the dynamic model. On this basis, the modal displacement time histories of the subframe were calculated by a dynamic simulation on virtual proving ground consisting of Belgian blocks, cobblestone road and washboard road. By combining the modal displacement time histories with modal stress tensors getting from normal mode analysis, the dynamic stress time histories of the subframe were obtained through modal stress recovery method.