Search Results

In this paper, a new gear preselect strategy of wet dual clutch transmission (DCT) is proposed by delaying the gear preselect to the time near the power shift time in order to create a seamless gear preselect. Software in the loop (SiL) method is used to investigate the proposed strategy. High fidelity 13 degree of freedom lumped inertia drivetrain models, i.e., synchronizer model and electro hydraulic model, are constructed and validated using laboratory test data. A closed loop control for electro hydraulic system is developed to control the clutch and synchronizer considering the optimum synchronizer trigger time. Furthermore, the model used in this study is constructed considering the valve spool dynamic in electro hydraulic system and the sleeve dynamic including axial drag force in synchronizer system. The genetic algorithm has been used to obtain the optimum trigger time which is close to the power shift time to sustain uninterrupted torque during gear shifting.

Hybrid electric vehicles (HEVs) are facing increased challenges of optimizing the energy flow through a vehicle system, to enhance both the fuel economy and emissions. Energy management of HEVs is a difficult task due to complexity of total system, considering the electrical, mechanical and thermal behavior. Innovative thermal management is one of the solutions for reaching these targets. In this paper, the potential of thermal management for a parallel HEV with a baseline control strategy under different driving cycles and ambient temperatures is presented. The focus of the investigations is on reducing fuel consumption and increasing comfort for passengers. In the first part of this paper, the developed HEV-model including the validation with measurements is presented. In the second part, the combined thermal management measures, for example the recuperation of exhaust-gas energy, engine compartment encapsulation and the effect on the target functions are discussed.

A vehicle thermal management system is required to increase the operating efficiency of components, to transfer the heat efficiently and to reduce the energy required for the vehicle. Vehicle thermal management technologies, such as engine compartment encapsulation together with grille shutter control, enable energy efficiency improvements through utilizing waste heat in the engine compartment for heating powertrain components as well as cabin heating and reducing the aerodynamic drag . In this work, a significant effort is put on recovering waste heat from the engine compartment to provide additional efficiency to the components using a motor compartment insulation technique and grille shutter. The tests are accelerated and the cost is reduced using a co-simulation tool based on high resolution, complex thermal and kinematics models. The results are validated with experimental values measured in a thermal wind tunnel, which provided satisfactory accuracy.

Hybrid electric vehicles (HEV's) are facing increasing challenges in optimizing the energy flow through a vehicle system, in order to improve both fuel economy and vehicle emissions. Energy management of HEV's is a difficult task due to the complexity of the total system in terms of electrical, mechanical and thermal behavior. In this paper, an advanced control strategy for a parallel hybrid vehicle is developed. Four main steps are presented, particularly to achieve a reduction in fuel consumption. The first step is the development of a highly complex HEV model, including dynamic and thermal behavior. Second, a heuristical control strategy is developed to determine the HEV modes and third, a State of Charge (SoC) leveling is developed with the interaction of a fuzzy logic controller. It is proposed to calculate the load point shifting of the Internal Combustion Engine (ICE) and the desired battery SoC.

Powertrain control strategies achieving high performance and better shift control depend critically on the available measurements taken directly from the sensors. For Dual Clutch Transmission (DCT), the clutch friction forces are very important to improve the shift quality. So the estimations are needed to be able to set up the shift control on the powertrain system. For better shift comfort, accurate information for the dual clutch transmission should be available to control the clutch pressure. Furthermore, torque sensors for rotating shafts cannot be used on production vehicles since they are expensive and enduring in the environment of the automotive system. This paper presents an Improved Proportional Integral (IPI) observer for estimation of the unknown forces acting on the clutch during shift processes as well as the non measured states. The estimated unknown forces can be used for the closed-loop control of the dual clutch transmission for better shift quality.

Hybrid electric vehicle (HEVs) represents a promising approach to reduce vehicle fuel consumption and exhaust emissions. However, due to the electric motor (EM) assistance, the engine load could be reduced and intermittent operation of engine is realizable in HEVs powertrain system. Consequently, the HEV powertrain heating-up process and engine fuel consumption will be changed accordingly. Therefore, the influences of the EM power and battery capacity on the hybrid powertrain heating-up process and the engine fuel consumption will be analyzed, and 2 methods for optimizing the heating-up process by applying the auxiliary heaters (AHs) and the modification of the energy management strategy are represented. The application of AHs can improve engine efficiency during heating-up; the controlling of the power flow from the AHs to the ICE cooling system is of special important.