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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.

Aiming at the problems of ineffective collision avoidance and vehicle instability in the process of vehicle emergency braking in road conditions with low adhesion and sudden change in adhesion coefficient, a stability-coordinated emergency braking and collision avoidance control system SEBCACS) is proposed. First, according to the motion of the ego vehicle and the target vehicle as well as the road adhesion conditions, a collision time model is proposed for evaluating the vehicle collision risk, and the expected deceleration required to avoid the collision is calculated. Then, the MPC method is used to calculate the yaw moment generated by the four-wheel braking force required to maintain vehicle stability according to the actual and reference yaw rate and side slip angle deviation. Then it is decided whether to implement additional yaw moment control according to the body stability evaluation results.

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.

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.

During the launch of a car, severe torsional vibration sometimes may occur in its driveline due to somewhat the slipping of the clutch, its intuitive sense for an occupant is the longitudinal vibration of the vehicle, referred to as the launch shudder whose characteristic frequency is from 5 to 25 Hz generally. As the main vibration sources of the driveline and its crucial nonlinear components, the variable stiffness and backlash of the gear meshing are considered, their impacts on the launch shudder are analyzed in this paper. Conformal mapping, finite element method and regression method etc. are the main approaches to calculate the variable meshing stiffness of a gear pair. If this stiffness is get, it can usually be substituted for its approximate analytical expression, just with finite harmonic terms, in Fourier Series form into Ordinary Differential Equations(ODEs) to calculate the vehicle responses with its nonlinearity considered.

The undesired shifting phenomenon(USP) occurs easily under the braking or climbing conditions etc., and its impact is the discomfort to the passengers or cause of vehicle's state contrary to the driver's intention, meanwhile, the wear of the clutch and synchronizer is increased, so their lifetime are greatly shortened. To the vehicle with dual clutch transmission (DCT), undesired shifting phenomenon will lead to frequent and unnecessary actuation of synchronizer for the use of pre-engagement synchronizer in the shifting control; therefore, its occurrence should be eliminated as far as possible. In this paper, the process of the undesired shifting of the vehicle with DCT is elaborated, then the generating cause of USP is described based on directed graph.

Difficulty of the Automatic Transmission(AT) is to properly control its clutch while the vehicle starts. An intelligent hierarchical controller is proposed in this paper. The upper of it is an intelligent PID controller based on a driver's experience and an expert's knowledge. It gives real time signals to the lower controller and coordinates the control between engine and clutch. The lower Variable Structure Fuzzy Controller (VSFC) executes the upper controller's direction signal.

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.

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.

In this paper the nonlinear system identification theory and method using neural networks are presented, the multilayer feedforward networks employed, the backpropagation learning algorithm proposed. The inputs of the networks are consisted of angular velocity and throttle angle, and outputs torque of the engine, finally the comparision of simulation result with that of experiment and other results that embody the effect of system identification are given. Relative studies revealed that the nonlinear system identification for the engine of automated automobiles using neural networks can be effective.

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.

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.

The city buses start and stop frequently, therefore significant amount of kinetic energy is wasted on friction plates. In order to retrieve this amount of energy, various feasible and efficient energy storage systems have been suggested by researchers to reuse the energy to improve the efficiency of the city bus. Due to small size, high energy density, cleanliness and easiness to absorb/reuse the energy, the storage system of flywheel is hopeful to be coming into wide use. In this paper, a dynamic model is analyzed to study the characteristics of the system using time series. Finally, comparison between simulation and experiment is given.