Search Results

In the intelligent airbag system, the detection accuracy of occupant position is the precondition and plays a vital role to control airbag detonation time and inflated strength during the crash. Through accurately analyzing the seat surface pressure distributions of different occupant sitting position and types, an occupant position recognition approach which purely uses occupant pressure distribution information measured by seat pressure sensors is presented with the method of Support Vector Machine. In the end, the distribution samples with different occupant sitting position and types are used to train and test the recognition approach, and the good validity and accuracy are shown in the experiments.

Vehicle Longitudinal Control (VLC) algorithm is the basis function of automotive Cruise Control system. The main task of VLC is to achieve a longitudinal acceleration tracking controller, performance requirements of which include fast response and high tracking accuracy. At present, many control methods are used to implement vehicle longitudinal control. However, the existing methods are need to be improved because these methods need a high accurate vehicle dynamic model or a number of experiments to calibrate the parameters of controller, which are time consuming and costly. To overcome the difficulties of controller parameters calibration and accurate vehicle dynamic modeling, a vehicle longitudinal control algorithm based on iterative learning control (ILC) is proposed in this paper. The algorithm works based on the information of input and output of the system, so the method does not require a vehicle dynamics model.

Lane-changing is a typical traffic scene effecting on road traffic with high request for reliability, robustness and driving comfort to improve the road safety and transportation efficiency. The development of connected autonomous vehicles with V2V communication provide more advanced control strategies to research of lane-changing. Meanwhile, four-wheel steering is an effective way to improve flexibility of vehicle. The front and rear wheels rotate in opposite direction to reduce the turning radius to improve the servo agility operation at the low speed while those rotate in same direction to reduce the probability of the slip accident to improve the stability at the high speed. Hence, this paper established Four-Wheel-Steering(4WS) vehicle dynamic model and quasi real lane-changing scenes to analyze the motion constraints of the vehicles.

In this paper, tensile experiments were performed on the dorsal and ventral skin of rats, and the mechanical properties of the skin in these two sites were compared and analyzed. A three-factor experimental protocol of site (dorsal and ventral), strain rate (0.71s-1, 7.1×10-3s-1), and sampling orientation (0°, 45° and 90° relative to the spine) was established for tensile test using the L6(31×22) orthogonal table modified from the standard orthogonal table L4 (23). Uniaxial tensile experiments were performed on rat skin samples to calculate the stress-strain curve. The failure strain energy was selected as the index, and the sum of squared deviations of the factors to the index was calculated by analysis of variance (ANOVA), and the contributions of the factors to the failure strain energy were evaluated. The results showed that the site factor has the largest effect on the tensile strain energy with a contribution of 88.9% and a confidence level of 95%.

Gear transmission is widely used in mechanical transmission system and acts an important role in automotive industry. Manufacturing errors, assembly looseness, gear wear issues may result in gear backlash, noise and fatigue damage seriously affecting efficiency and service life of gear transmission. For gear transmission assembled, it is important to monitor the conditions of gear meshing and prevent the occurrence of dangerous situations. How to define the issues of gear tooth wear, misaligned bearing, gear eccentricity, backlash, and how to find faulty planetary gear sets and specific issues existing in gear transmission are meaningful and significant to ensure the quality of product. This paper starts from the analysis on gearing mechanism. Based on the behaviors represented by the issues, gear tooth wear, misaligned bearing, gear eccentricity and backlash are demonstrated and explained in detail.

Acute repetitive traumatic brain injury (rTBI) can occur in a pedestrian collision when the head hits the vehicle and the ground twice, as well as in a serial rear-ended collision in a very short period. This study established an animal model of acute rTBI to investigate the cumulative effects of repetitive brain injury under different combinations of impact levels. 117 adult male Sprague–Dawley (SD) rats (190±20g) were divided into control, single impact, and repeated impact groups, with the single impact group was divided into three subgroups of mild, moderate, and severe. And the repeated impact group was divided into nine subgroups by combining mild, moderate, and severe. The kinematic response parameters of the rat’s head were captured by a high-speed camera and acceleration sensors. Modified neurological severity score (mNSS) was performed at 6h after final injury, and the severity of injury was quantified using the abbreviated injury scale (AIS).

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.

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.

Collision avoidance technology is one of the key areas in the longitudinal safety research of intelligent vehicles. For the research of collision avoidance system, the existing methods usually use the evaluation index based on time interval or braking process to carry out risk assessment. In order to overcome the shortcomings of the formulas for describing the longitudinal hazard degree established in most studies, such as great differences, inconsistent standards and weak normalization, a comprehensive evaluation method for the longitudinal hazard in front-impact scenarios is established. This method takes into account both the analysis of time interval and braking process, and considers the non-linear variation of the longitudinal hazard degree with the real-time distance and speed of two vehicles. It can describe the longitudinal hazard degree of vehicles in dangerous traffic scenarios.

At the collision moment, a driver’s lower extremity will be in different foot position, which leads to the different posture of the lower extremity with various muscle activations. These will affect the driver’s injury during collision, so it is necessary to investigate further. A simulated collision scene was constructed, and 20 participants (10 male and 10 female) were recruited for the test in a driving simulator. The braking posture and muscle activation of eight major muscles of driver’s lower extremity (both legs) were measured. The muscle activations in different postures were then analyzed. At the collision moment, the right leg was possible to be on the brake (male, 40%; female, 45%), in the air (male, 27.5%; female, 37.5%) or even on the accelerator (male, 25%; female, 12.5%). The left leg was on the floor all along.

The high popularity of automobiles has led to frequent collisions. According to the latest statistics of the United Nations, about 1.25 million people worldwide die from road traffic accidents each year. In order to improve the safety of vehicles in driving, the active safety system has become a research hotspot of various car companies and research institutions around the world. Among them, the more mature and popular active security system are Forward Collision Warning(FCW) and Autonomous Emergency Braking(AEB). However, the current active safety system is based on traditional sensors such as radar and camera. Therefore, the system itself has many limitations due to the shortage of traditional sensors. Compared to traditional sensors, Vehicle to Everything (V2X) technology has the advantages of richer vehicle parameter information, no perceived blind spots, dynamic prediction of dangerous vehicle status, and no occlusion restriction.

With rapid development of the automobile industry and the growing maturity of the automotive electronic technologies, the distributed-traction electric vehicle with four-wheel-distributed steering/braking/traction systems is regarded as an important development direction. With its unique chassis structure, it is the ideal benchmark platform used to evaluate active safety systems. The distributed-traction electric vehicle with four-wheel-distributed steering system is essentially full drive-by-wire vehicle. With its flexible chassis layout and high control degrees-of-freedom, the full drive-by-wire electric vehicle acted as a kind of redundant system is an ideal platform for the research of integrated control. In this treatise, the longitudinal dynamics of the electric vehicle as well as its lateral and yaw motions are controlled simultaneously.

With the rapid development of science and technology, the automobile industry is developing rapidly, and intelligent networking and autonomous driving have become new research hotspots. The safety and efficiency of vehicle driving has always been an important research topic in the transportation field. Due to reducing the participation of drivers, autonomous vehicles can reduce traffic accidents caused by human factors. While the development of intelligent networking can achieve information sharing between vehicles, and improve driving efficiency to a certain extent. Based on the game theory and the minimum safe distance condition, this paper establishes a lane changing decision model of intelligent network-connected autonomous vehicles, puts forward a game payoff function and analyzes the game strategy.

As a new brake-by-wire solution, the electro-booster (Ebooster) brake system can work with the electronic stability program (ESP) equipped in the real vehicle to realize various excellent functions such as basic force boosting (BFB), active braking and energy recovery, which is promoting the development of smart vehicles. Among them, the BFB is the function of Ebooster's servo force to assist the driver's brake pedal force establishing high-intensity braking pressure. After the BFB function failure of the Ebooster, it was not possible to provide sufficient brake pressure for the driver's normal braking, and eventually led to traffic accidents. In this paper, a compensation redundancy control strategy based on ESP is proposed for the BFB failure of the self-designed Ebooster.

Electrification and intelligence are the important development directions of vehicle techniques. The Electro-Mechanical Brake Booster (Ebooster) as a brake booster which is powered by a motor, can be used to replace the traditional vacuum booster. Ebooster not only improves the intelligence level of vehicle braking and significantly improves the braking performance, but also adapts to the application in new energy vehicles and facilitates coordinated regenerative braking. However, Ebooster cannot complete pedal decoupling independently. It needs to cooperate with other components to realize pedal decoupling. In this paper, a pedal decoupling control algorithm for regenerative brake, which is based on the coordination control of Ebooster and ESP, is proposed. First, regenerative braking strategy is designed to distribute the hydraulic brake force and regenerative braking force.

Rattle noise as an error state of cabin noise in vehicles has become an important topic both in research and application. In engineering, the commonly used method to evaluate and detect rattle issues is greatly dependent on experts’ personal auditory perception. People judge a noise simply as “loud” and “not loud” or “qualified” and “unqualified.” A more objective method needs to be developed to eliminate the randomness of subjective evaluation. In this paper, a rig test of the seatbelt retractors was performed, and simulated random excitation was applied to the test samples through the MB vibration test bench in a semi-anechoic chamber. The rattle noises were recorded by HEAD SQuadriga II. Various methods were employed to identify and assess the severity of rattle noise on seatbelt retractors.

Most of the skin injuries caused by traffic accidents, sports, falls, etc. are in the intermediate strain rate range (1-100s-1), and the injuries may occur at different sites, impact velocities, and orientations. To investigate the multifactorial mechanical properties of rat skin at intermediate strain rates, a three-factor, three-level experimental protocol was established using the standard orthogonal table L9(34), which includes site (upper dorsal, lower dorsal, and ventral side), strain rate (1s-1, 10s-1, and 100 s-1), and sampling orientation (0°, 45°, and 90° relative to the spine). Uniaxial tensile tests were performed on rat skin samples according to the protocol to obtain stress-stretch ratio curves. Failure strain energy was selected as the index, and the influence of each factor on these indexes, the differences between levels of each factor, and the influence of errors on the results were quantified by analysis of variance (ANOVA).

It’s hard to achieve complete self-driving using hand-crafting generalized decision-making rules, while the end-to-end self-driving system is low in complexity, does not require hand-crafting rules, and can deal with complex situations. Modular-based self-driving systems require multi-task fusion and high-precision maps, resulting in high system complexity and increased costs. In end-to-end self-driving, we usually only use camera to obtain scene status information, so image processing is very important. Numerous deep learning applications benefit from multi-task learning, as the multi-task learning can accelerate model training and improve accuracy with combine all tasks into one model, which reduces the amount of calculation and allows these systems to run in real-time. Therefore, the approach of obtaining rich scene state information based on multi-task learning is very attractive. In this paper, we propose an approach to multi-task learning for semantics, geometry and motion.

It is generally considered that the material properties of foam are the most important factors in vehicle seat, which affect the human-seat interface pressure. Therefore, only the role of foam is usually considered when the finite element method is used to simulate the human-seat interface pressure. In this paper, the mechanical properties and the modeling method of commonly used seat cover material were studied. The models of the seat with and without cover were established respectively according to the real-vehicle seat geometric data, and the human-seat interface pressure was simulated after the seat and human model consisting of bones, soft tissue and skin were assembled. The simulation result was compared with the actual measurement results from test, which verified the accuracy of the simulation and the role of seat cover in the human-seat interface pressure simulation.

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.