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With more and more countries proposing timetables for stopping selling of fuel vehicles, China has also issued a “dual-slope” policy. As electric vehicles are the most promising new energy vehicle, which is worth researching. The integration and control of the motor and gearbox have gradually become a hot research topic due to low cost with better performance. This paper takes an electric vehicle equipped with permanent magnet synchronous motor and two-gear automatic transmission without synchronizer and clutch as the research object.

Reliability-based design optimization (RBDO) has been widely used to obtain a reliable design via an existing CAE model considering the variations of input variables. However, most RBDO approaches do not consider the CAE model bias and uncertainty, which may largely affect the reliability assessment of the final design and result in risky design decisions. In this paper, the Gaussian Process Modeling (GPM) approach is applied to statistically correct the model discrepancy which is represented as a bias function, and to quantify model uncertainty based on collected data from either real tests or high-fidelity CAE simulations. After the corrected model is validated by extra sets of test data, it is integrated into the RBDO formulation to obtain a reliable solution that meets the overall reliability targets while considering both model and parameter uncertainties.

To design and optimize the vehicle driveline is necessary to decrease the fuel consumption and improve dynamic performance. This paper describes a methodology to optimize the driveline design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A new and flexible tool for modeling multi-domain systems, Modelica, is used to carry out the modeling and analysis of a vehicle, and the multi-domain model is developed to determine the optimum design in terms of fuel economy, with determinability. Secondly, a robust optimization is carried out to find the optimum design considering uncertainty. The results indicate that the fuel economy and dynamic performance are improved greatly.

For the purpose of lessening fuel consumption, engine noise, shift jerk and clutch friction work in the shift process of Automatic Mechanical Transmission (AMT), a fuzzy-bang bang dual mode control strategy for engine rotate speed is put forward in this paper, which takes the advantages of time optimal control and fuzzy control. The combined control strategy is applied to the shift process control of AMT test minibus named SC6350 and proved to be successful by the experimental results.

The shift quality is one of the most important factors that affect the vehicle performances of comfort, ride and drivability for vehicles equipped with dual clutch transmission (DCT). Assessing the shift quality first and then optimizing shift control strategy and algorithm by the guidance of assessment results to improve the vehicle performance is a useful idea for the development of DCT and other types of automatic transmissions. This paper defines the shift quality assessment criteria in detail for DCT from the control point of view. A shift quality assessment system and a DCT vehicle model used for validation of assessment system are built with MATLAB/Simulink tools. Through the co-simulation of DCT vehicle model and assessment system, the shift quality control objectives, namely the expected control range of each assessment criterion, are determined, which provide reference and guidance for the optimization of DCT shift control.

A good starting quality for AMT (Automated Manual Transmission) vehicles means that the vehicle is started quickly and smoothly on the premise of protecting powertrain system. The starting quality is closely related to the vehicle ride comfort and the service life of powertrain system. In order to improve the starting quality, a good idea is evaluating the starting process firstly and then optimizing the control strategy. However this method has two problems to be solved. The first one is how to define a series of objective criterions to judge the starting quality, and the other is how to select a suitable algorithm to optimize the starting control. This paper focuses on the starting quality assessment and optimization of AMT vehicles. First, the assessment criterions for starting quality are defined in detail from the control point of view and a corresponding assessment system is created.

Ride comfort is simply defined as the vibration performance of the vehicle which is excited by road surface roughness, generally as the vehicle moves at specific constant velocity over the road profile. Ride comfort was an important index for heavy truck, due to long distance transfer and long time driving. In order to improve the ride comfort of a heavy truck, a detailed model, including flex frame, chassis suspension, cab suspension, powertrain, etc., was built and assembled by MSC.ADAMS software. Simulation and testing data were consistent very well, which showed the correctness of the model. The optimization of chassis and cab suspension including the stiffness of the leafspring, the damping of the shock absorber, etc. was carried out to improve the ride comfort of the vehicle. The ride comfort testing was carried out on the proving ground to verify the effectiveness the optimization results. The testing results shows that the ride comfort has been improved after tuning.

This investigation presents a methodology to develop and optimize shift process control strategy to improve shift quality as perceived by drivers during power-on upshift events for Dual Cultch Transmission (DCT) vehicles. As part of the first study, the main factors affecting shift quality during shifting process under typical working conditions are analyzed. And taking the power-on upshift as example, dynamic model of DCT shifting process is build. An Integrated control strategy is proposed for power-on upshift, which during torque phase slipping revolving speed controller is adapted to harmonically control two clutches power switching process, and during Inertial phase engine torque is regulated to synchronize with the value of target gear while holding the oncoming clutch pressure. Oncoming clutch oil pressure gradient in torque phase and engine torque reducing target decrement in inertial phase are chosen as controlled quantity.

Particle swarm optimization (PSO) is a relatively new stochastic optimization algorithm and has gained much attention in recent years because of its fast convergence speed and strong optimization ability. However, PSO suffers from premature convergence problem for quick losing of diversity. That is to say, if no particle discovers a new superiority position than its previous best location, PSO algorithm will fall into stagnation and output local optimum result. In order to improve the diversity of basic PSO, design of experiment technique is used to initialize the particle swarm in consideration of its space-filling property which guarantees covering the design space comprehensively. And the optimization procedure of PSO is divided into two stages, optimization stage and improving stage. In the optimization stage, the basic PSO initialized by Optimal Latin hypercube technique is conducted.

This paper presents the relationship between suspension and steering systems and wheels, and proposes the vehicle dynamics modeling method. A vehicle dynamics model combined with the suspension K&C test data of a concrete vehicle was built based on the method. The simulation results show that the method is correct and feasible, and the dynamics model performed characteristics of the suspension and steering systems with high precision can be used for the followup simulation and optimization.

Transmission gear whine noise is one of the main noise problems in powertrain NVH, which is caused by dynamic meshing force of gear pairs, it acts as transmission error. Due to the coupling effects of transmission gears, shaft, bearings and housing, it needs comprehensive management from many aspects to solve the problem of gear whine noise. Aiming at gear whine noise of a 4-speed AMT used in electric bus, the main noise sources is identified by using the order tracking analysis approach firstly. Secondly, gear misalignment and contributions of system deformation to the misalignment is analyzed by means of simulation tools, and the factor is taken into account in the subsequent gear modification design. At last, based on the improved Smith slice method, the calculation model of transmission error of helical gears is established.

Starting control has become a troublesome issue in the developing field of the control system for heavy-duty trucks, due to the complexity of vehicle driving and the variability of driver's intention. The too fast clutch engagement may result in serious impact, influence on the comfort and fatigue life, and even the engine flameout, while the too slow clutch engagement may lead to long time of friction, the increased temperature, and accelerated wear of friction pair, as well as influence on the power performance and fatigue life[1]. Therefore, the key technique of starting control is clutch engagement control, for which the fuzzy PID based optimization of starting control for AMT clutch is proposed, with the pneumatic AMT clutch of heavy-duty trucks as the research object.