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As a newly designed hybrid transmission, DHT (Dedicated Hybrid Transmission) owns the advantages of compact structure, multi-modes and excellent comprehensive performance. Compared with the traditional add-on hybrid transmission with one single motor, DHT uses one independent generator for engine starting and speed adjusting which can be largely improve the driving performance in the mode changing process. Based on the series-parallel DHT with wet clutch for power coupling, this paper firstly analyses the power coupling clutch device functionalities from the power flow viewpoint under normal and limp home condition. And for the changing process from series to parallel mode, a clutch coordination control strategy is designed by combining generator fast speed adjusting with clutch accurately pressure controlling to fulfill the fast driver intension response and clutch protection.

In order to improve the robustness and stability of autonomous vehicle at high speed, a path tracking approach which combines front steering and differential braking is investigated in this paper. A bicycle model with 3-DOFs is established and a linear time-varying predictive model using front steering as its control input can be derived. Based on model predictive theory, the path tracking issue using linear time-varying model predictive control can be transformed into an online quadratic programming problem with constraints. The expected front steering angle can be obtained from online moving optimization. Then the direct yawing control is adopted to treat two types of differential braking control. The first one investigates steady-state gain of yaw rate in linear 2-DOFs vehicle model, and designs a stable differential braking controller which is based on reference yaw rate.

During a car launch, the driving torque from driveline acts on brake disk, and may lead the pad to slip against the disk. Especially with slow brake pedal release, there is still brake torque applies on the disk, which will retard the rotation of disk, and under certain conditions, the disk and pad may stick again, so the reciprocated stick and slip can induce the noise and vibration, which can be transmitted to a passenger by both tactile and aural paths, this phenomenon is defined as brake groan. In this paper, we propose a nonlinear dynamics model of brake for bidirectional, and with 7 Degrees of Freedom (DOFs), and phase locus and Lyapunov Second Method are utilized to study the mechanism of groan. Time-frequency analysis method then is adopted to analyze the simulation results, meanwhile a test car is operated under corresponding conditions, and the test signals are sampled and then processed to acquire the features.

For high levels autonomous driving functions, the Decision Layer often takes on more responsibility due to the requirement of facing more diverse and even rare conditions. It is very difficult to accurately find a safe and efficient lane change timing when autonomous vehicles encounter complex traffic flow and need to change lanes. The traditional method based on rules and experiences has the limitation that it is difficult to be taken into account all possible conditions. Therefore, this paper designs a lane-changing decision algorithm based on data-driven and machine learning, and uses the DQN (Deep Q Network) algorithm in Reinforcement Learning to determine the appropriate lane-changing timing and target lane. Firstly, the scene characteristics of the highway are analyzed, the input and output of the decision-making model are designated and the data from the Perception Layer are processed.

For the DCC (Dynamic Chassis Control) system, in addition to the requirement of ride and comfort, it is also necessary to consider the requirement of handling and stability, and these two requirements are often not met at the same time. This poses a great challenge to the design of the controller, especially in the face of complex working conditions. In order to solve this problem, this paper proposes a comprehensive DCC controller that considers road roughness class recognition. Firstly, a quarter vehicle model is established, the road surface roughness is calculated from the vertical acceleration of the wheels measured by the sensors. Then we calculate the autocorrelation function and the Fourier transform to estimate the PSD (Power Spectral Density) to get the road roughness class. Then control algorithms are designed for the vertical motion control, roll control and pitch control.

The traditional automotive torque converter (TC) is equipped with a single-blade stator, at the suction side of which there is an apparent boundary layer separation at stalling condition because of its large impending angle. The separation flow behind the suction side of stator blade is found to create large area of low-energy flow which blocks effective flow passage area, produces more energy losses, decreases impeller torque capacity and transmission efficiency. It is found effective to suppress the boundary layer separation by separating the original single-blade stator into a primary and a secondary part. The gap between them guides high-energy flow at the pressurized side of the primary blade to the suction side of the secondary one, which helps to make boundary layer flow stable. As a result, the impeller torque capacity and torque ratio at low-speed ratio increase tremendously at the cost of little drop of maximum efficiency.

Subframe is an important part of automobile chassis, which is connected with body, suspension control arm, powertrain mount, etc. The dynamic stiffness value of the connection point is an important performance index of the subframe, which affects the vibration of the vehicle body. This paper introduces the basic concept and related theory of dynamic stiffness, derives the theoretical formula of dynamic stiffness, and analyzes the frequency response of the key points of the subframe. In view of the fact that the dynamic stiffness of the subframe of a certain vehicle model is not up to the standard at some connection points, the dynamic stiffness CAE simulation analysis is carried out to determine the frequency range of insufficient dynamic stiffness and the connection points that need to be optimized.

In this paper,the flywheel is considered to be linear elastic composition in accordance with its operating characteristic, mechanical and mathematical model are presented,the finite element method is employed to carry out the numerical analysis of steady and unsteady stresses within the high speed flywheel in the regenerative braking system of a city bus,and these provide the basis foŕ its structural modification and further rational design.

Jet-wake flow and secondary flows are undesirable in torque converters as they are responsible for flow losses and flow nonuniformity; that is, jet-wake flow and secondary flows negatively affect the torque converter performance. Therefore, it is very important to investigate and minimize the undesirable flows to decrease flow losses in torque converter. However, the existing studies are limited to employ geometry design parameter modifications rather than focusing on the actual causes and intrinsic physical mechanism that generate the flows to reduce the flow losses. In this paper, Calculation model of a torque converter is presented first and a three dimensional CFD code was used to simulate the internal flow field of a torque converter. The simulation results coincide with experimental measurements, which verifies the validity of the method. Based on flow field calculation results, the internal flow field of impeller, turbine and stator were analyzed, respectively.

Numerical simulation of instabilities of brake systems based on complex mode analysis is presented in this paper. The theoretical analysis shows that the friction-induced unsymmetrical system stiffness matrix results in instability, and nonlinear static analysis plays a key role in the overall analysis. The frictional study shows how unstable mode occurs, in addition to that the nonlinear effects are taken into considerations and the one variable regression function is employed to set up the relative predict functions.

The vehicle system is actually a strongly nonlinear system with stochastic parameters. In this paper, the nonlinearities of suspension, tire and seat are analyzed, and the nonlinear dynamics model of driver-vehicle system with 8 degrees of freedom (DOFs) is built. The bifurcation and chaotic motion of the deterministic system under Sinusoid excitations considering the time delay between the front and rear tires are studied. Then, the stochastic feature of the equivalent stiffness and damping coefficients of suspension, tire and seat are assumed to be the normal distribution, and the nonlinear model with random parameters is obtained. The nonlinear dynamics of stochastic nonlinear driver-vehicle system is analyzed and compared through numerical simulation.

A novel hydraulic transmission system-Hydraulic Energystorage Transmission System(HESTS) which contains a Hydraulic Continuously Variable Transmission(HCVT) and a flow controllable accumulator is proposed. The power flows of the HESTS has been analyzed. Computer simulations show the potentialities of improving fuel economy of a vehicle with a HESTS. A fuzzy logic controller with two regulating factors is developed to improve the performance of the HESTS with variable loads.

Although Hydrostatic Transmission System (HTS) had been used in many places, such as machine tools, agriculture machinery, construction machinery, and vehicles, it had not been used in good performance. Twenty years ago many people began to design new hydrostatic transmission with higher efficiency. Hydrostatic Energy Storage Transmission System (HESTS) is one of new hydrostatic transmission system with higher efficiency. HESTS is more fit for being used in vehicle that is always running in undulating ground or starting and braking frequently. Construction of vehicular HESTS was analyzed, mathematical model of vehicular HESTS was established. The needed control strategies of vehicular HESTS were analyzed because there are many variables would be controlled in the new transmission system.

Most centrifugal pendulum vibration absorber (CPVA) research focuses on the horizontal or vertical plane, ignoring the influence of gravity. However, with the wide application of CPVAs in the automobile industry, some gravity-related problems have been encountered in practice. In this study, employing the second kind of Lagrange equation, the differential equation of motion of a CPVA is established, and the first-order approximate analytical solution is solved using the method of multiple scales. The mathematical relations among the excitation torque amplitude and phase, gravity influence, absorber trajectory shape, absorber position, viscous damping coefficient, and mistuning level parameters are provided for study. Specifically, the second-order responses of four absorbers and two absorbers in a gravity field are studied, and the influence of the change in the torque excitation phase on the response of the absorber is thoroughly analyzed.

In this paper, the intelligent control theory and method using neural networks are presented, the multilayer feedforward networks employed, the back propagation learning algorithm proposed. Finally the angular velocity control result of the hydrostatic drive system of secondary regulation with such type of control is provided. Relative studies revealed that the intelligent control for the system using neural networks can be effective.

The cruise control as one of promising vehicle active control has been receiving a considerable attention in recent years, so the related problems are discussed in this paper. Mathematical model of the engine under the steady state and general dynamics equation of the Continuously Variable Transmission(CVT) are given, the regulating principle of the operating state of the engine is analyzed, and the conjugate gradient method employed to solve the optimal control problem of the vehicle in the cruise control is described, so the operating state of the engine could be controlled. At end of paper, some results are provided to verify the approach based on the vehicular powertrain with a hydromechanical CVT.

Centrifugal Pendulum Vibration Absorber (CPVA for short) is used to absorb torsional vibrations caused by the shifting motion of the engine. It is increasingly used in modern powertrains. In the research of the dynamic characteristics of the CPVA, it is necessary to obtain the real motion of the pendulum to compensate the fitting performance of mathematical model. The usual method is to install an angle sensor to measure the movement of the pendulum. On the one hand, the installation of the sensor will affect its movement to a certain extent, so that the measurement results do not match the actual motion. On the other hand, the motion of the pendulum is not only the rotational motion around the rotational axis of the CPVA rotor, but also has translation relative to it. As a result, it is difficult to obtain accurate motion only by the angle sensor. We proposed a non-contact centrifugal pendulum motion measurement method.

In this paper, the system identification theory and method using dynamic neural networks are presented, the multilayer feedforward networks employed, the backpropagation with adaptive learning rate algorithms proposed. Finally the comparision of network output with that of the hydrostatic drive system of secondary regulation is given, and output error, sum-squared error et al, or the results that embody the effect of system identification given sine input to it are provided.