Search Results

In summer, when vehicle parks in direct sunlight, the closed cabin temperature would rise sharply, which affects the occupants step-in-car comfort Solar powered vehicle parking ventilation system adopts the solar energy to drive the original ventilator. Thus, the cabin temperature could be dramatically decreased and the riding comfort could be also improved. This research analyzed the modified crew cabin thermal transfer model. Then the performance of the solar powered ventilation system is analyzed and optimized combined with the power supply characteristics of the photovoltaic element. The storage and reuse of the solar power is achieved on condition that the cabin temperature could be steadily controlled. The research shows that, the internal temperature is mainly affected by the solar radiation intensity and the environment temperature.

With the increasingly serious global environmental and energy problems, as well as the increasing number of vehicles, pure electric vehicles with its advantages of environmental protection, low noise and renewable energy, become an effective way to alleviate environmental pollution and energy crisis. Due to the current pure electric vehicle power battery technology is not perfect, the range of pure electric vehicle has a great limit. Through the braking energy recovery, the energy can be reused, the energy utilization rate can be improved, and the battery life of pure electric vehicles can be improved. In this paper, a pure electric vehicle is taken as the analysis object, and the whole vehicle analysis model is built. Through the comparative analysis, based on the driver's braking intention and vehicle running state, the braking energy recovery control strategy of double fuzzy control is proposed.

Correct shifting schedule of vehicle coasting mode play a vital role in improving vehicle comfort and economy. At present, the calibration of the transmission shifting schedule ignores the impact of vehicle’s dynamic mass. This paper proposes a method for optimizing the shifting schedule of the coasting modes with gear based on the dynamic mass identification of the vehicle. This method identifies the dynamic mass of the vehicle during driving and substitute them into the process of solving the shifting schedule parameters. Then we get the optimal shifting schedule. At first, establish the Extended Kalman Filter to Pre-process the experimental data, reducing errors caused by excessive data fluctuations. Then, establishing a weighted squares estimation model based on particle swarm optimization to identify the dynamic mass of the vehicle.

In the field of active safety, the active four-wheel-steering (4WS) system seems to be an attractive alternative and an effective tool to improve the vehicles' handling stability in lane-keeping control performance. Under normal using condition, the vehicle's lateral acceleration is comparatively small, and the mathematic relationship between the small side force excitation and the small slip angle of the tire is in the linear region. Furthermore, the effects of roll, heave, and pitch motions are neglected as well as the dynamic characteristics of the tires and suspension system in this work. Therefore, the linear quadratic control (LQC) theory is used to ensure that the output of the 4WS control system can keep track of the desired yaw rate and zero-sideslip-angle response can also be realized at the same time.

Discretionary lane changing is commonly seen in highway driving. Intelligent vehicles are expected to change lanes discretionarily for better driving experience and higher traffic efficiency. This study proposed to optimize the decision-making and trajectory-planning process so that intelligent vehicles made lane changes not only with driving safety taken into account, but also with the goal to improve driving comfort as well as to meet the driver’ s expectation. The mechanism of how various factors contribute to the driver’s intention to change lanes was studied by carrying out a series of driving simulation experiments, and a Lane-Changing Intention Generation (LCIG) model based on Bi-directional Long Short-Term Memory (Bi-LSTM) was proposed.

To prevent braking recession, heavy commercial vehicles are often equipped with fluid auxiliary braking devices, such as hydraulic retarder. Hydraulic retarder can convert the vehicle’s kinetic energy to the fluid heat energy, which can enormously alleviate the main brake’s workload. The traditional hydraulic retarder can provide enough braking torque but has a delay during the braking. In this paper, a new type of magnetorheological fluid (MR fluid) hydraulic retarder is introduced by replacing the traditional fluid with magnetorheological fluid because of its linear braking torque and quick response. By changing the magnetic field intensity, it is easier to control the braking torque than the traditional hydraulic retarder. The rise of magnetorheological fluid temperature during the braking period will reduce the hydraulic retarder’s performance.

The anti-roll bar is an important structural component of the automobile, which can effectively prevent the automobile from rolling and improve the safety of the automobile during steering. In the design of the current anti-roll bar, the stiffness is determined by empirical or oversimplified mathematical models, often not reaching the optimal value. In this paper, eight parameters are used to determine the structure of the anti-roll bar. Combining the Deformation Energy theorem and Castigliano’s theorem, a mathematical model of the stiffness is established. The optimal solution and corresponding parameter values of the mathematical model are obtained by nonlinear programming and genetic algorithm. The influence of structural parameters on the anti-roll bar stiffness is analyzed, and the regular pattern of design is obtained. In addition, the finite element method is used to verify the stiffness solution model.

In automatic driving application, the velocity planner can be considered as a key factor to ensure the safety and comfort. One of the most important tasks of the velocity planner is to simulate the velocity characteristics of human drivers. In this paper, two Driver In-the-Loop (DIL) experiments are designed to explain velocity characteristics of human drivers. In the first experiment, static obstacles are placed on both sides of the straight road to shorten the cross range that vehicles can driver across. Moreover, different cross ranges are set to study the influence of the steering wheel error. In the second experiment, velocity characteristics are investigated under the condition of different road widths and curvatures in a U-turn road contour. In both tests, different drivers’ preview behavior is analyzed through the operation of throttle, braking, and steering.

Driving comfort is one of the most important indexes for automobile comfort. Driving posture comfort is closely related to the drivers' joint angles and joint torques. In present research, a new method is proposed to identify the most comfortable driving posture based on studying the relation between drivers' joint angles and joint torques. In order to truly reflect a driving situation, the accurate human driving model of 50 percent of the size of Chinese male is established according to the human body database of RAMSIS firstly. Biomechanical model based on accurate human driving model is also developed to analyze and obtain dynamic equations of human driving model by employing Kane method. The joint torque-angle curves of drivers' upper and lower limbs during holding wheel or pedal operation can be obtained through dynamic simulation in the MATLAB. Through curve-fitting analysis, the minimum joint torque of a driver' limb and the optimal joint angel can be found.

Braking energy recovery is an important method for Battery Electric Vehicle (BEV) to save energy and increase driving range. The vehicle braking system performs regenerative braking control based on driver operations. Different braking operations have a significant impact on energy recovery efficiency. This paper proposes a method for planning the braking process of a BEV based on the Intelligent Vehicle Infrastructure Cooperative System (IVICS). By actively planning the braking process, the braking energy recovery efficiency is improved. Vehicles need to decelerate and brake before entering a curve. The IVICS is used to obtain information about the curve section ahead of the vehicle's driving route. Then calculating the reference speed of the curve, and obtaining the vehicle's braking target in advance, so as to actively plan the vehicle braking process.

With the increase of car ownership and the complex and crowded parking environment, it is difficult for drivers to complete the parking operation quickly and accurately, which may cause traffic accidents such as vehicle collisions and road jams because of poor parking skills. The emergence of an automatic parking system can help drivers park safely and reduce the occurrence of safety accidents. In this paper, the neural network identifier on the control method of an adaptive integral derivative of a neural network is proposed for an automatic parallel parking system with front-wheel steering is studied by using MATLAB/Simulink environment, and the simulation is carried out. Firstly, according to vehicle parameters and obstacle avoidance constraints, the minimum parking space, and parking starting position are calculated. Meanwhile, the path planning of parallel parking spaces is carried out by quintic polynomial.

Magnetorheological fluid (MRF) is used as the transmission medium of the hydraulic retarder. The rheological properties are regulated by changing the magnetic field to achieve accurate control of the retarder's braking torque. Under the action of the external magnetic field, the flow structure and performance of the MRF retarder will be changed in a short time. The apparent viscosity coefficient increases by several orders of magnitude, the fluidity deteriorates and the heat generated by the brake cannot be transferred through the liquid circulation, which will affect the braking torque of the retarder. Changing the surface area of the stator also has an influence on the braking torque of the retarder and the wall heat dissipation. In this study, the relationship between the braking torque of the MRF retarder and the stator surface area of the retarder was analyzed.

Driver distraction detection is crucial to driving safety when autonomous vehicles are co-piloted. Recognizing drivers’ behaviors that are highly related with distraction from real-time video stream is widely acknowledged as an effective approach mainly due to its non-intrusiveness. In recently years, deep learning neural networks have been adopted to by-pass the procedure of designing features artificially, which used to be the major downside of computer-vision based approaches. However, the detection accuracy and generalization ability is still not satisfying since most deep learning models extracts only spatial information contained in images. This research develops a driver distraction model based on a two-stream, spatial and temporal, convolutional neural network (CNN).

In order to avoid the braking recession on heavy commercial vehicles caused by the long-distance continuous braking of the main brake, the hydraulic retarder is widely used as an important brake auxiliary device in various heavy commercial vehicles to improve the vehicle safety. However, the hydraulic retarder not only has the advantages of large braking torque and good stability, but also has the disadvantages of poor retarding ability at low rotating speed, braking lag and difficulty in accurately controlling the braking torque. This paper introduces a new type of hydraulic retarder. The new retarder replaces the oil in the retarder with magnetorheological fluid and applies a magnetic field in the retarder arrangement space, so that slows down the vehicle by using the rheological properties of the magnetorheological fluid under the magnetic field.

On-road testing of driving performance of the urban bus was carried out, and a representative urban bus driving cycle was developed after on-road testing, according to the test results. Then, the vehicle simulation software AVL CRUISE was used to simulate the dynamic behavior of the urban bus. It involves the simulation of complete drive train system and the driver behavior. The model is validated by comparing the results of the simulation to the results of the field test. Then the developed driving cycle is evaluated by fuel consumption resulted from the simulation and engine bench test on fuel economy.

Operating level of a metal-belt CVT mainly rest with the ECU. Conventional control strategies which were obtained from tests or PID controller can not correspond to the driver’s intention or provide various driving environments. It is considered that control targets of metal-belt CVT could be distinguished by a speed ratio, line pressure and starting element till now. Running performance of automobile with a CVT mainly depends on the speed ratio control. An adapted fuzzy logic ratio control algorithm is suggested and optimized. A throttle position and its changing rate will be inputs of the FLC to meet the driver’s intention and make the intelligent control come true. A fuzzy logic line pressure control algorithm is also suggested and optimized corresponding to the complicated high line pressure control.

Squeal noise in vehicle disc brakes is perceived by comsumers as both annoying and warranty cost. The mechanism is considered a mode coupling phenomenon also referred to as coalescence. In this paper, the system eigenvalues have been computed using a technique based on the • nite element method in order to obtain the dynamical properties of the disc brake assembly. The simulated squeal results were compared with the brake noise test that was in accordance with SAE J2521 standard and showed good correlation for some squeal frequencies which indicated that the research on disc brake squeal using complex mode could predict squeal propensity of the disc brake. Among the methods that have been used to control squeal noise, increasing the system damping has been shown to be very effective. The most commonly used method to increase system damping consists of attaching multi-layer laminates on the back of the brake pads.

Semi-active suspension has been widely applied in commercial vehicle suspension in order to get good riding comfortableness. Fuzzy logic control (FLC) has been widely applied in the field of kinetic control because control rule of FLC is easy to understand. But the gain of fuzzy rules and adjustment of membership functions usually depend on experts' experiences and repeated experiments, thus the fuzzy rules and membership functions has strong subjectivity, also are easily affected by environment of experiments, so the main problem of fuzzy logic controller design is selection and optimization of fuzzy rules and membership functions. Genetic Algorithms (GA) is the algorithm that searches the optimal solution through simulating natural evolutionary process and is one of the evolution algorithms which have most extensive impact.

Hydraulic retarder has been widely applied on military vehicles and heavy commercial vehicles because of it could provide great brake torque and has lasting working time [1]. In order to reduce driver's frequent actions in braking process and prevent hydraulic retarder system from overheating, it is need to apply constant braking torque control, this control target has a strict requirement to hydraulic control system design. Many parameters often require repeated test to determine, which increases the R&D cost and extends the research cycle. This paper tries to find a time-efficient research method of hydraulic retarder control system through studying on a heavy military vehicle hydraulic retarder system. Hydraulic retarder model is set up through test data. The hydraulic control system is built based on AMESim. Controller model is set up based on PID control. The whole vehicle brake model is built based on MATLAB/Simulink.

People, vehicles and circumstances are the three key factors, which affect transportation systems. Offering more information to the driver and helping him observe on all sides so that he can make decisions correctly are of great importance for reducing accidents. According to the present traffic regulations, in this paper we focus on the rules and process used during steering and proposed to implement them in a car information central control system based on CAN. A comparison of the brake time between brake by driver and by radars revealed the great interest of using ECUs connected by CAN network.