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Wet clutches are widely used in automotive systems. They are essential parts of automatic transmissions, modern All-Wheel-Drive systems or dual-clutch transmissions. Regardless of the area of application, a good knowledge of clutch friction behaviors is crucial for the clutch control system development. This paper considers two important factors of the wet clutch dynamics: coefficient of friction behavior and thermal dynamics. An Active Limited Slip Differential wet clutch with carbon fiber-based friction lining material is experimentally characterized by using a precise wet clutch setup. The characterization of the coefficient of friction behavior includes influence of clutch slip speed, applied force, and friction surface temperature. The clutch thermal dynamics is characterized based on the heat power balance law applied to the clutch separator plate with a variable heat transfer coefficient. The results of the thermal model experimental validation are presented, as well.

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.

A step-ratio automatic transmission alters torque paths for gearshifting through engagement and disengagement of clutches. It enables torque sources to run efficiently while meeting driver demand. Yet, clutch thermal energy during gearshifting is one of the contributors to the overall fuel loss. In order to optimize drivetrain control strategy, including the frequency of shifts, it is important to understand the cost of shift itself. In a power-on upshift, clutch thermal energy is primarily dissipated during inertia phase. The interaction between multiple clutches, coupled with input torque truncation, makes the decomposition of overall energy loss less obvious. This paper systematically presents the mathematical analysis of clutch thermal energy during the inertia phase of a typical single-transition gearshift. In practice, a quicker shift is generally favored, partly because the amount of energy loss is considered smaller.

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.

This paper presents a practical and straightforward method of identifying geometry parameters of a cam-like lever-based electromechanical dual-clutch actuator, with application to actuator dynamics model parameterization. The lever-based actuator resembles a cam mechanism in that a movable roller fulcrum, driven by an electromotor through a ball-screw, drives the lever by direct contact along the lever profile. This necessitates the identification of the lever profile geometry in order to accurately model the mechanism dynamics. The identification method is based on the measured basic lever mechanism dimensions, experimentally recorded input-output response of the lever mechanism during unloaded operation, observed geometric constraints satisfied during operation, and common CAD software tools to conduct a CAD-based mechanism synthesis and position analysis.

Dual Clutch Transmissions with dry electromechanically actuated clutches have emerged on the market recently. In order to provide their favorable operation in terms of the clutch torque control, it is very important to have a good knowledge on the system behavior related to the actuator dynamics, the dry friction coefficient behavior, and the thermal dynamics. This paper describes two test rigs developed to support the research work on a dry dual clutch with a lever-based electromechanical actuation system. The first test rig (actuation system test rig) provides a basis for a comprehensive multi-step identification of the actuation system parameters and characterization of the overall system behavior. This test rig includes a modified dual clutch assembly including a built-in sensor for the purpose of direct normal force measurement.

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.

In order to support active limited slip differential (ALSD) modeling work, a test rig of a DC motor-actuated ALSD has been developed. The test rig is equipped with a torque servomotor that provides a precise closed-loop control of the clutch slip speed, as well as with sensors of clutch torque, and DC motor position and current. In addition to the test rig, a precise wet clutch experimental setup has been developed by using the differential hardware. The setup provides direct measurements of the clutch pack axial force, the separator plate temperature, and the press plate axial position. The paper describes the ALSD test rig and the wet clutch experimental setup, presents and analyzes characteristic experimental results, and outlines the main ALSD modeling results.

Magnetorheological fluid (MRF) clutches are expected to be used in several automotive systems such as auxiliary engine devices, active differentials, and automatic transmissions. An experimental MRF clutch has been developed at the University of Zagreb, in order to support MRF clutch modeling and control research. The paper first presents calculation of the main clutch design parameters and describes the clutch mechatronic system. Next, the clutch static and dynamic behaviors are experimentally characterized. Finally, a model of MRF clutch dynamics is outlined, and characteristic model validation results are presented.

The bond graph method is used to model kinematics of various one-mode and two-mode series-parallel configurations of hybrid electric vehicle transmissions. Based on the derived speed and torque equations, a comparative analysis of hybrid transmissions steady-state behaviors is conducted. An example of control-oriented bond graph modeling of hybrid transmission dynamics is presented, as well.

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 paper deals with the design of shift scheduling maps based on dynamic programing (DP) optimization algorithm. The recorded data related to a delivery vehicle fleet are used, along with a model of delivery truck equipped with a 12-gear automated manual transmission, for an analysis and reconstruction of the truck-implemented shift scheduling patterns. The same map reconstruction procedure has been applied to a set of DP optimization-based operating points. The cost function of DP optimization is extended by realistic clutch energy losses dissipated during shift transients, in order to implicitly introduce hysteresis in the shift scheduling maps for improved drivability. The different reconstructed shift scheduling maps are incorporated within the truck model and validated by computer simulations for different driving cycles.

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 detailed experimental validation has been carried out to point to limitations of static wet-clutch friction model for typical clutch engagement transients. The model accuracy can be increased by incorporating the fluid film dynamics, as done in the lumped-parameter dynamic clutch model developed at the University of Purdue. That model is extended herein in order to increase its accuracy especially in the case of grooved clutches. The extensions include a description of clutch actuator dynamics and introduction of an empirical scaling factor for the fluid film thickness state equation. More rigorous treatment of fluid dynamics for the grooved clutch is also presented.

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

This paper proposes a method for multi-objective parameter optimization of piecewise linear time profiles for control of Automatic Transmission (AT) shifts and presents results obtained on an example of a powertrain with a 10-speed automatic transmission. The paper first outlines the powertrain dynamics model. Then, the AT control trajectory optimization approach is outlined and employed with the aim of getting insights into the optimal shift control profiles and related performance. The parameter optimization problem is to find parameters of piecewise linear shift control profiles, which provide a trade-off between the shift comfort and performance. The optimization problem is solved by using the multi-objective genetic algorithm MOGA-II incorporated within modeFRONTIER environment.

This paper considers using linear quadratic regulation (LQR) for multi-input control of the Automatic Transmission (AT) upshift inertia phase. The considered control inputs include the transmission input/engine torque, oncoming clutch torque, and traditionally not used off-going clutch torque. Use of the off-going clutch has been motivated by discussed Control Trajectory Optimization (CTO) results demonstrating that employing the off-going clutch during the inertia phase along with the main, oncoming clutch can improve the upshift control performance in terms of the shift duration and/or comfort by trading off the transmission efficiency and control simplicity to some extent. The proposed LQR approach provides setting an optimal trade-off between the conflicting criteria related to driving comfort and clutches thermal energy loss.

Automatic transmission (AT) upshift control performance in terms of shift duration and comfort can be improved during the inertia phase by coordinating the off-going clutch together with oncoming clutch and engine torque. The performance improvement is highest in low gear shifts (i.e., for high ratio steps), which are typically performed with open torque converter. In this paper, a discrete-time, linear quadratic regulation (LQR) is applied during the upshift inertia phase, as it provides an optimal multi-input/multi-output control action with respect to the prescribed cost function. The LQR law is based on a reduced-order drivetrain model, which is applicable to actual transmissions characterized by a limited number of available state measurements. The reduced-order model includes the linearized torque converter model. The shift duration is ensured by precise tracking of a linear-like oncoming clutch slip speed reference profile.