Clutch Engagement Control Research Articles

Plug‐In Hybrid Electric Vehicle Energy Management with Clutch Engagement Control via Continuous‐Discrete Reinforcement Learning

Energy management strategy (EMS) is a key technology for plug‐in hybrid electric vehicles (PHEVs). The energy management of certain series–parallel PHEVs involves the control of continuous variables, such as engine torque, and discrete variables, such as clutch engagement/disengagement. Herein, a control‐oriented model is established for a series–parallel plug‐in hybrid system with clutch engagement control from the perspective of mixed‐integer programming. Subsequently, an EMS based on continuous‐discrete reinforcement learning (CDRL), which enables simultaneous output of continuous and discrete variables, is designed. During training, state‐of‐charge (SOC) randomization is introduced to ensure that the hybrid system exhibits optimal energy‐saving performance in both high and low SOC. Finally, the effectiveness of the proposed CDRL strategy is verified by comparing EMS based on charge‐depleting charge‐sustaining (CD‐CS) with rule‐based clutch engagement control and dynamic programming (DP). In the simulation results, it is shown that, under a high SOC, the CDRL strategy proposed in this article can improve energy efficiency by 8.3% compared to CD‐CS, and the energy consumption is just 6.6% higher than the global optimum based on DP, while under a low SOC, the numbers are 4.1% and 3.9%, respectively.

Study on the Engagement Characteristics and Control Strategy of High Speed Difference Dry Friction Clutch

In the short/vertical take-off and landing aircraft propulsion system, the vertical take-off/landing and rapid flight are switched through the engagement and disconnection of the dry friction clutch. The smooth and rapid connection of the friction clutch is crucial for the mobility and reliability of this type of aircraft. However, the friction clutch vibrates and generates a large amount of heat at high speed, which affects the engagement performance of the clutch. In practice, when the engagement pressure rises quickly, the clutch engagement time is short, and the temperature rise is small, but the impact torque is large, and vice versa. In view of this problem, with a short/vertical take-off aircraft dry friction clutch as the research object, considering the nonlinear variation of friction coefficient and lift fan load torque, the dynamics model and temperature field model of the high speed difference dry friction clutch are established to analyze the clutch engagement time, impact torque, and temperature change. The engagement test at the high speed of the clutch shows that the simulation results of the kinetic model and temperature field model are consistent with the test results. To realize low temperature rise, low impact torque, and short engagement time, the variable slope engagement pressure control method is proposed. Compared with the traditional fixed slope engagement pressure, the proposed variable slope engagement pressure can reduce the engagement time, impact torque and temperature rise simultaneously. The research results can provide a reference for the friction clutch engagement control of short-range take-off and landing aircraft, reduce the development cost of such aircraft, and improve the reliability of the design.

Automatic Clutch Engagement Control for Parallel Hybrid Electric Vehicle

Automatic clutch engagement control is essential for all kinds of vehicle power transmissions. The controllers for vehicle power transmissions may include model-based or model-free approaches and must provide high transmission efficiency, fast engagement and low jerk. Most vehicle automatic transmissions are using torque converters with transmission efficiencies up to 96%. This paper presents the use of fuzzy logic control for a dry clutch in parallel hybrid electric vehicles. This controller can minimize the loss of power transmission since it can offer a higher transmission efficiency, up to 99%, with faster engagement, lower jerk and, thus, higher driving comfortability with lower cost. Fuzzy logic control is one of the model-free schemes. It can be combined with AI algorithms, neuro networks and virtual reality technologies in future development. Fuzzy logic control can avoid the complex modelling while maintaining the system’s high stability amid uncertainties and imprecise information. Experiments show that fuzzy logic can reduce the clutch slip and vibration. The new system provides 2% faster engagement speed than the torque converter and eliminates 70% of noise and vibration less than the manual transmission clutch.

Decoupling internal model control for the robust engagement of clutches

Research on the robustness of clutch engagement control is attracting considerable interest because of its wide applications in advanced powertrains. Internal model control (IMC) is advantageous because it can handle model errors and external disturbances with light computational loads. However, during clutch engagement, two control inputs (engine output torque and clutch transmitted torque) and two system outputs (driving speed and the driven part of the clutch) are coupled; moreover, the two reference inputs are considerably different. A method for directly decoupling and stabilizing multi-input multi-output systems controlled by a two-degree-of-freedom (2DOF) IMC is proposed based on the construction of V-canonical matrices. The proposed method allows simple expressions for the control algorithm to be obtained without computing an inverse matrix that is used conventionally. Two filters, considering both the reference inputs and system characteristics, are independently designed considering the decoupling operation. The simulation results show that the proposed decoupling 2DOF IMC gains a considerably less tracking error and better robustness to model error and disturbance compared to classical 2DOF IMC and model predictive control. The performance is validated via dynamometer experiments.

Optimization Control of CVT Clutch Engagement Based on MPC

As an important part of continuously variable transmission (CVT) vehicle power transmission system, drive, neutral and reverse (DNR) wet clutch has the function of transmitting or interrupting vehicle power. However, due to the complex and variable working conditions of the clutch, it is difficult to achieve precise control of the clutch by the traditional control strategy. To solve this problem, a clutch control optimization algorithm based on model predictive control (MPC) is proposed. In order to identify and track the driver's launching intentions, a driver's launching intentions recognition system based on fuzzy neural network (FNN) is designed. The impact degree and friction work are taken as the evaluation standard of clutch control. The clutch controller is designed by using MPC control strategy, and the control effect is compared with the adaptive fuzzy neural network (AFNN) strategy. Finally, the validity of the control strategy is verified by simulation model and vehicle test. The results show that compared with the AFNN control strategy, the MPC control strategy can effectively control the clutch engagement and improve the vehicle launching quality.

Joint structure for the real-time estimation and control of automotive dry clutch engagement

In this paper, real-time identification of the dry-clutch torque characteristics model in automotive systems is investigated. The proposed algorithm focused to provide the direct capability to update the clutch torque characteristics model by using engine speed and torque as measurable signals in real-time, within a multiple model predictive control loop. First, the clutch torque is estimated with some uncertainty. Then, it is proposed a new trust-region based identification approach which is robust enough to cover this uncertainty. The aim of the MPC controller is to ensure a comfortable lockup by avoiding engine stall and reasonable engagement time. The effectiveness and performance of the approach are demonstrated through the real-time model simulations in various conditions.

Optimal launching-intention-aware control strategy for automated clutch engagement

Clutch engagement control is critical during launching process in a vehicle equipped with an automated manual transmission (AMT), which is a problem including muti-objective optimization and nonlinear control. In this paper, a optimal launching-intention-aware control strategy is proposed for clutch engagement. Firstly, a launching-intention-aware machine (LIAM) based on artificial neural network (ANN) is designed to identify the driver’s launching intentions. Then the optimal laws of clutch engagement for different launching conditions are obtained based on the dynamic programming (DP), which regard friction loss, vehicle shock, angular acceleration of engine and engine torque as the optimizing indexes. Next, a slidingmode controller (SMC) is designed for the clutch engagement. Finally, the performances of the optimal laws and the SMC are validated by the joint simulation of Simulink-AMESim, and the results show that the requirements of vehicle launching are met. The proposed clutch engagement control strategy would provide a better theoretical support for the practical-extended application of AMT.

Engagement Control of Automated Clutch for Vehicle Launching Considering the Instantaneous Changes of Driver's Intention

Engagement control of automated clutch is essential during launching process for a vehicle equipped with an automated manual transmission (AMT), and instantaneous changes in the driver's launching intention make it more complicated to control the clutch. This paper studies the identification of the driver's launching intentions, which may change anytime, and proposes a clutch engagement control method for vehicle launching. First, a launching-intention-aware machine (LIAM) based on artificial neural network (ANN) is designed for real-time tracking and identifying the driver's launching intentions. Second, the optimal engagement strategy for different launching intentions is deduced based on the linear quadratic regulator (LQR), which figures out a compromise between friction loss, vehicle shock, engine speed, clutch speed, and desired vehicle speed. Third, the relationship between transmitted torque and clutch position is obtained by experiments, and a sliding-mode controller (SMC) is designed for clutch engagement. Finally, the clutch engagement control strategy is validated by a joint simulation model and an experiment bench. The results show that the control strategy reflects the driver's launching intentions correctly and improves the performance of vehicle launching.

Automatic calibration process for optimal control of clutch engagement during launch

ABSTRACTLaunching a vehicle is related to changing acceleration. High acceleration is desired for sporty driving behavior, however, jerk as change of acceleration and change of jerk are major sources of discomfort. Modern double-clutch transmissions allow to shape the acceleration transition by controlling the torque transmitted by the clutch, which is why the question arises about an optimal transition law for the acceleration and optimal calibration of automatic transmissions. A bi-criterion optimization problem is formulated to account for both sportiness and comfort, where the latter criterion is defined as deviation from an ideal acceleration transition. For finding such an optimal transition, another tri-criterion optimization problem is set up and solved analytically. The calibration of the transmission TCU is then performed in a SIL (Software-in-the-Loop) environment where results demonstrate the validity of the proposed approach.

Engine clutch engagement control for a parallel hybrid electric vehicle using sliding mode control scheme

In this paper, the dynamic model of the engine clutch engagement process is studied and a sliding mode control scheme is then developed. It is shown that the relationship between the chamber pressure and the clutch piston displacement during the engine clutch engagement process can be modeled as a second-order system. A sliding mode controller can then be designed based on the bound information of the uncertain system parameters and load force, in the sense that not only the strong robustness with respect to system uncertainties and non-linearities but also good tracking performance can be obtained. Finally, the comparative simulation results are presented to verify the good performance and effectiveness of the proposed control scheme.

Robust and two-level (nonlinear) predictive control of switched dynamical systems with unknown references for optimal wet-clutch engagement

Modeling and control of clutch engagement has been recognized as a challenging control problem, due to nonlinear and time-varying dynamics, that is, switching between two discontinuous dynamic phases: the fill and the slip. Furthermore, the reference trajectories for obtaining an optimal clutch engagement are not a priori known and may require adaptation to varying operating conditions. Two (nonlinear) model predictive control strategies are proposed based on the partial or full (non)linear identification of these two phases. First, a local linear model of the fill phase is identified and a robust model predictive control is designed to account for the consequent uncertainty in the slip phase. Second, (non)linear models of both the fill and the slip phases are identified and a two-level (nonlinear) model predictive control controller is proposed, where two (nonlinear) model predictive control controllers are designed for the two phases tracking references generated and continuously adapted by high-level iterative learning controllers. The robust and two-level (nonlinear) model predictive controls are validated on a real clutch. The results obtained from the real setup show that the proposed control strategies lead to an optimal engagement of the wet-clutch system.

Fast and smooth clutch engagement control for dual-clutch transmissions

Automotive dual-clutch transmissions use two gear shafts and two clutches to perform automated gear shifts at a high comfort level. The two objectives of the clutch engagement controller are to realize a fast clutch engagement to reduce the gear shifting time, and a smooth clutch engagement to accurately track the demanded torque without a noticeable torque dip. This research work presents a new controller design that explicitly separates the control laws for each objective by introducing clutch engagement phases. Simulations and experiments in a test vehicle show that the control objectives are realized with a robust and relatively simple controller.

Optimal control of dry clutch engagement based on the driver’s starting intentions

This paper explores the association between the driver’s starting intentions and control of dry clutch engagement during the vehicle launch in order to develop an intelligent automated mechanical transmission system. The optimal engagement laws are deduced by finding a compromise between the friction loss, the shock intensity, the engine torque and the engine angular acceleration, based upon the extremum value theorem. The optimal parameters of clutch engagement are adjusted for the value of the shock intensity. The driver’s starting intentions, which can be divided into three patterns, namely fast starting, medium-speed starting and slow starting, are associated with optimal control of clutch engagement according to fuzzy control theory. It is demonstrated that optimal control of dry clutch engagement can reflect the driver’s starting intentions correctly. The obtained optimal accelerator opening has more advantages than the actual accelerator opening, which can be adopted as the ideal input of the vehicle with an intelligent automated mechanical transmission system.

A Control Strategy on Starting up of Vehicle with Automatic Manual Transmissions (AMT)*

Recently, starting control takes an important role in the automatic manual transmission systems; clutch engagement control is the key of it. In order to improve the starting performance of AMT vehicle, clutch dynamic response must be control during the slipping phase. Therefore, this paper puts forward a control strategy for the dry clutch engagement process, considered as a finite time optimal control problem. The main idea of this strategy is to obtain a linear quadratic state feedback controller by solving the optimal control problem. The performance obtained with the proposed controller are compared with those achievable by means of a classical open loop control strategy. Moreover, different starting operating conditions are used to test the controller performance. Numerical simulations shows the good performance obtained by the proposed controller, which guarantees fast engagement, minimize the slip losses, reduce the fuel consumption and improve in the shift quality.

Optimal Piecewise-Linear Control of Dry Clutch Engagement

This paper proposes a novel piecewise linear feedback control strategy for the dry clutch engagement process. Based on a dynamic model of the powertrain system, the controller is designed by minimizing a quadratic performance index subject to constraints on the normal force, normal force derivative, and engine speed. The resulting model predictive controller is shown to consist of a piecewise linear feedback control and can be tuned so that fast engagement, small friction losses and smooth lock-up are achieved. Numerical results show the good performance of the closed-loop system.

Fuzzy Control of Clutch Engagement for Automated Manual Transmission

SUMMARY This paper presents a fuzzy control system for the clutch engagement of an automated manual transmission. The servomechanism is assembled with a three-port pneumatic pressure-proportional valve and a position-sensing cylinder which control the release-lever displacement of 25 mm within the position preciseness of 0.1 mm against maximum spring load of 2kN. The fuzzy system is skillful to estimate the driver's will from the accelerator pedal operation. The servomechanism is mounted on a commercial vehicle with 4-ton pay-load. The system parameters are set up by bond graphs simulation and empirical performance tests are carried by using an oil-hydraulically operated engine-vehicle testing rig with a maximum torque capacity of 400 Nm.

Electropneumatic clutch servomechanism and its fuzzy control for automated manual transmission

This paper describes an application of electropneumatically operated servomechanism with fuzzy control intelligence to the sophisticated control of clutch engagement for an automated manual transmission. The servomechanism is assembled with a three port pneumatic pressure proportional valve and a position sensed cylinder which controls arelease lever of 25mm stroke within the position preciseness of 0.1mm under a maximum spring load of 2kN. The fuzzy system estimates driver's will only from the accelerator pedal operation. The performance of the system is evaluated from the starting characteristics by using an oil hydraulically operated engine-vehicle simulating test rig with a maximum torque capacity of 400N·Em.