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Clutch wear is dominantly manifested as the reduction of friction plate thickness. For dry dual clutch with position-controlled electromechanical actuators this affects the accuracy of normal force control because of the increased clutch clearance. In order to compensate for the wear, dry dual clutch is equipped with wear compensation mechanism. The paper presents results of experimental characterization and mathematical modeling of two clutch wear related effects. The first one is the decrease of clutch friction plate thickness (i.e. increase of clutch clearance) which is described using friction material wear rate experimentally characterized using a pin-on-disc type tribometer test rig. The second wear related effect, namely the influence of the clutch wear compensation mechanism activation at various stages of clutch wear on main clutch characteristics, was experimentally characterized using a clutch test rig which incorporates entire clutch with related bell housing.

The paper presents the estimator design procedures for automotive power train systems based on the adaptive Kalman filter. The Kalman filter adaptation is based on a simple and robust algorithm that detects sudden changes of power train variables. The adaptive Kalman filter has been used to estimate the SI engine load torque and air mass flow, and also the tire traction force and road condition. The presented experimental results indicate that proposed estimators are characterized by favorable response speeds and good noise suppression abilities.

Thermal expansion of a clutch pack with position-controlled actuation can affect the accuracy of clutch normal torque control, because it causes an increase of the clutch normal force for the given actuator position. The paper presents an experimental characterization and mathematical modeling of the dry dual clutch thermal expansion effects. The experimental data have been collected by using a clutch/transmission test rig. The acquired data point to two separate, mutually opposite thermal expansion effects. The first effect relates to increase of the clutch clearance with temperature growth, while the second one includes decrease of press plate and engagement bearing positions for a given clutch torque and a rising temperature (i.e. the clutch torque rises with temperature growth and a constant actuator position). In order to explain and describe these two effects, a geometry analysis of the clutch, focused on thermal expansion, is carried out.

An adaptive electronic throttle control strategy is proposed with the aim to provide robust and precise positioning of the throttle plate. The control strategy consists of a PID controller and a nonlinear compensator of friction and limp-home effects. The adaptation mechanism includes auto-tuning and self-tuning algorithms. The auto-tuner provides automatic adjustment of the key control strategy parameters without any prior knowledge of the process parameters. The self-tuning algorithms are based on the permanent, on-line estimation of the DC motor armature resistance, battery voltage, and limp-home position. The control strategy and the adaptation algorithms are verified experimentally.

The vehicle dynamics control systems are traditionally based upon utilizing wheel brakes as actuators. However, there has been recently strong interest in the automotive industry for introduction of other vehicle dynamics actuators, in order to improve the overall vehicle stability, responsiveness, and agility features. This paper considers various actuators such as active rear and central differentials and active front and rear steering, and proposes design of related yaw rate control systems. Different control subsystems such as reference model, feedback and feedforward control, allocation algorithm, and time-varying controller limit are discussed. The designed control systems are verified and compared by computer simulation for double lane change and slalom maneuvers.

This paper deals with a thorough analysis of using two fundamentally different algorithms for optimization of electric vehicle (EV) fleet charging. The first one is linear programming (LP) algorithm which is particularly suitable for solving linear optimization problems, and the second one is dynamic programming (DP) which can guarantee the global optimality of a solution for a general nonlinear optimization problem with non-convex constraints. Functionality of the considered algorithms is demonstrated through a case study related to a delivery EV fleet, which is modelled through the aggregate battery modeling approach, and for which realistic driving data are available. The algorithms are compared in terms of execution time and charging cost achieved, thus potentially revealing more appropriate algorithm for real-time charging applications.

The paper proposes an energy management control strategy for a Extended Range Electric Vehicle comprising an internal combustion engine, two electrical machines, and three clutches. The control strategy smoothly combines a rule-based strategy, extended with a battery state-of-charge (SoC) controller, with an instantaneous optimization algorithm based on equivalent consumption minimization strategy (ECMS). In addition to engine on/off logic, the rule based controller includes rules which are extracted from the global dynamic programming-based off-line optimization results. The control strategy is verified by means of computer simulation for different operating modes and certification driving cycles, and the simulation results are compared with the dynamic programming optimization results which are considered as globally optimal.

A dynamic programming-based algorithm is developed and used for off-line optimization of range extended electric vehicle power train control variables over standardized certification driving cycles. The aim is to minimize the fuel consumption subject to battery state-of-charge constraints and physical limits of different power train variables. The control variables to be optimized include engine torque and electric machine speed, as well as a variable that selects the power train operating mode. The optimization results are presented for four characteristic certification driving cycles and characteristic vehicle operating regimes including electric driving during charge depleting mode, hybrid driving during charge sustaining mode, and combined/blended regime.

The paper presents a detailed design procedure of an SI engine load torque estimator based on an adaptive Kalman filter. The adaptation mechanism is based on a simple and robust load torque change detection algorithm. The presented simulation and experimental results point out that the estimator is characterized by a fast response and good noise suppression. The proposed estimator is used to establish a fast load torque compensation path in an idle speed control system. The presented simulation and experimental results show that this yields a significant improvement of idle speed control performance