Dual Clutch Research Articles

Adaptive Gearshift Control for Dual Clutch Transmissions Based on Hybrid Physical and Data Driven Modeling

Adaptive Gearshift Control for Dual Clutch Transmissions Based on Hybrid Physical and Data Driven Modeling

Energy loss and efficiency investigations of a dual clutch transmission based on adaptive experiment and analytical simulation

Energy transfer improvement and energy consumption reduction are getting more crucial in the automotive sector. As one of the essential elements directly influencing energy transfer in the powertrain system, transmission losses have been widely analyzed with both simulation and experimental approaches. For a better characterization of individual losses, this paper investigates and compares most of the available analytical models for further system implementation. Regarding laboratory experiments, an adaptive sampling strategy is presented and analyzed for various operating conditions. Compared to the traditional factorial design, the applied Gaussian Process Regression (GPR) delivers both estimations and their predictive variances in the entire experiment process. Besides, new measurement candidates can be determined with the prior information from GPR model. The analytical simulation and adaptive measurement are employed to investigate a seven-speed transmission. With both approaches, a detailed discussion about total transmission losses and individual loss mechanisms are performed under various operating conditions.

Common transmission theory and wide application

Gear and belts/chains are the most common solution for modern mechanical devices. The allowable stress and gear ratio are two of the main factors that decide the performance of the ear section for transmission. The allowable stress can be calculated by bending stress and contact stress from design criteria. The performance of the belt solution is decided by the belt/chain material, center distance and the belt length. The allowable strength of the belt/chain solution is strongly related to the materials selected. With the current study of belts and gears, the related factors could be calculated to design the optimum shape and material. Dual clutch transmission (DCT) and continuously variable transmission (CVT) are two widely applied transmissions with gear and belt/chain solutions that are introduced in the research. The advantages of DCT could be the reliability and high transmission efficiency of the gear solution and the space and energy efficiency of belt/chain structure advantages of the CVT. Both DCT and CVT could be applied in different conditions to maximize the specific performance.

An active knee orthosis with a variable transmission ratio through a motorized dual clutch

An active knee orthosis with a variable transmission ratio through a motorized dual clutch

Study on nonlinear dynamics characteristics of dual speed dual clutch transmission system based on bond graph

The variable speed transmission system employs compound planetary gear trains and clutches. Compared to traditional aviation transmission systems, the added control parts in the variable transmission system result in a stronger coupling between components and more complex dynamic response characteristics. Modeling using the central mass method is complex and abstract. This study proposes a bond graph-based method for modeling and analyzing the dynamic behavior of the variable transmission system. The transmission system is divided into multiple component-level real-time dynamic models, and obtain a nonlinear multi-energy domain shift dynamic models based on energy flow paths coupling. The mathematical model is numerically solved using the Runge-Kutta method. Simulation results show that there is a delay in the speed response during the shifting process. Further analysis reveals that this “give and take” phenomenon is related to the mechanical structure and passive working principle of the one-way clutch. Subsequently, the time-domain response of the output speed under the hydraulic loading characteristic curves of linear, exponential, S-shaped, and composite functions, as well as the clutch torque, were studied. The impact of different hydraulic loading durations based on the exponential curve on component speed and torque was also analyzed. The simulation results provide a theoretical basis for designing low-shift impact, high-reliability, and high-performance variable transmission systems.

Fault Detection Strategy for Fork Displacement Sensor in Dual Clutch Transmission via Deep Long Short-Term Memory Network

Detecting the fork displacement sensor fault is critical for ensuring the reliability and safety of a dual clutch transmission (DCT). In this paper, a deep learning method is proposed to monitor the state of the fork displacement sensor. Firstly, the fork displacement prediction algorithm is developed based on the deep long short-term memory (LSTM) network using the driving data of a DCT vehicle. Secondly, the synchronizer control system model is constructed to imitate the fork displacement sensor fault as the experimental vehicle works in normal condition and the collected data lacks of faulty sensor signal. Finally, the residual is obtained by comparing the predicted fork displacement and the measured sensor information. The sensor fault is detected as the residual exceeds the predetermined threshold. Results show the fork displacement prediction algorithm can accurately estimate the synchronizer position. And the fault detection method can detect the fork displacement sensor fault timely and accurately.

Real-Time Optimization of Gear Shift Trajectories Using Quadratic Programming for Electric Vehicles With Dual Clutch Transmission

The main focus of this paper is a method for real-time optimization of the gear shift trajectories for electric vehicles (EVs) with dual clutch transmissions. First, a driveline model was arranged for each gear shift process. The states in each gear shift process can be predicted through these models. An objective function is composed of a frequency-shaped jerk to minimize the shift shock and take into account the bandwidth limit of the lower-level controller. Equality constraints are defined for smooth model changes during the gear shift processes. Moreover, the conditions needed to reflect the driver's pedal input (which can be changed in real-time) is composed of an equality constraint. In addition, inequality constraints are constructed to limit the maximum value of the torque, torque rate, and jerk during gear shift processes. Finally, the problem is formulated in quadratic programming (QP) form. The gear shift trajectories and feedforward inputs are generated by obtaining an optimal solution through the QP solver. The performance of the proposed algorithm is verified through testbench experiments.

Test method for determining the scuffing capacity of oils with reduced oil volume

Previous studies by several researchers have shown that the aging of the transmission fluid in dual clutch transmissions has a major impact on the wear protection of the highly loaded tribological contacts. Depending on the transmission design, oil sump temperature, transmitted torque, rotational speed and oil volume, the scuffing ability decreases significantly. Since typically only limited quantities of oil from gearbox tests are available to evaluate oil condition with respect to wear protection properties, available analytical standards are currently limited to methods such as viscometry, TAN, elemental analysis, and IR. A test method is presented that can be used to determine the gear scuffing load capacity of transmission fluids with a reduced oil volume. For this purpose, a standard test rig is modified to reduce the test oil volume from 1.25 liters, as specified in the public standards, to 0.5 liters. The applicability of the reduced test oil volume is demonstrated and the remaining scuffing wear protection of several used oil samples from durability testing is presented. A comparison of the tribological results with the chemical oil analysis results shows the advantage of direct testing of the oil's service properties.

Dynamic Behaviour of an Automotive Dual Clutch Transmission during Gear Shift Maneuvers

The paper presents a model for the torsional dynamics of an automotive driveline equipped with a Dual Clutch Transmission (DCT), focusing on the gear rattle phenomenon arising during the transients of engagement and disengagement of the clutches, and during the synchronizing manoeuvres. This vibro-acoustic phenomenon, particularly annoying in automotive transmissions, can be accentuated by the presence of many unloaded gears in this type of gearbox. Dual Clutch Transmission systems are today largely diffused in the car automatic transmissions, permitting fast gear shifts and avoiding the interruption of the drive torque. The study is conducted by adopting a tribo-dynamic model with lumped parameters, considering the oil lubricant between the teeth of the unloaded gears acting as a damper during the impacts. A layout of a gearbox with six speed ratios has been assumed, in which a dual clutch system transmits the drive torque alternatively between the various gear pairs in the odd and even branches. The results of the numerical simulations show that this kind of transmission system is characterised by hard rattling behaviour, particularly during the rapid phases of clutches engaging/disengaging and during the gears synchronisation. Some solutions to attenuate the torsional vibrations, and therefore the rattling behaviour of the unloaded gears in a DCT gearbox, can be analysed by the proposed model to determine, as example, the time duration of the gear shift phase or of the pre-selection phase to the next gear, as well as to identify the optimal lubrication conditions of the gear pairs during the gear shift transients.

Pseudo-spectral optimization and model predictive control of vehicle shift process with dual clutch transmission

To improve the shift quality of dual clutch transmission (DCT) vehicles and reduce the jerk and sliding friction in the shift process, a real-time planning of clutch optimal engagement trajectory and control method in the shift process is proposed. This method combines pseudo-spectral optimization, machine learning, and model predictive control. First, considering the jerk, sliding friction work, and shift time as the optimization indices, the adaptive pseudo-spectral method is employed to optimize the engagement trajectory of the clutch during the shift process. Based on the optimal trajectory data set, a gradient boosting decision tree-based real-time planning method for the clutch target engagement trajectory is proposed. Second, a model predictive control strategy for the shift process is proposed based on the DCT system model to track the optimal target trajectory in real-time. Simulations and experiments reveal that the proposed target engagement trajectory planning method can plan the clutch target engagement trajectory for various accelerator pedal openings and initial clutch speed states in real-time, and the proposed model predictive control method can accurately track the target trajectory. Compared with the original vehicle strategy, under 35% and 65% accelerator pedal opening, the maximum absolute value of jerk produced by the proposed strategy was reduced by 31.06% and 31.46%, respectively, and the sliding friction work was reduced by 22.87% and 23.24%, respectively. The shift times of the proposed strategy under 35% and 65% accelerator pedal openings were 19.12% and 20.69% lower than that of the original vehicle strategy, respectively.

Synthesis of the Energy-Saving Dry Dual Clutch Control Mechanism

A promising direction in developing up-to-date transport vehicles is the use of transmissions, an essential element of which is a dual-clutch. Improving functional performance, energy efficiency, and environmental friendliness are relevant and require appropriate research. The object of study is a dry dual-clutch working with a manual transmission with high energy efficiency. In the proposed design scheme, a rotary lever and a movable carriage can change the structural diagram of the force interaction between the pressure spring and the clutch discs. The developed mathematical model of the clutches control mechanism allowed for analyzing the process of controlling the dual-clutch transmissions (DCT) and obtaining functional dependencies between pushing forces in friction pairs and the carriage position. As a result, a method for synthesizing DCT was proposed to ensure the transmission of a given torque. Furthermore, it was determined and numerically proven that the same radial movement of the carriage when switching-on the clutches does not guarantee equal loading for the frictional discs of each clutch. This fact increases the uneven dynamics of torque and disc wear. Overall, the synthesis of the energy-saving dry dual-clutch control mechanism providing the same clutch margin for each clutch was developed. The method can be generalized and applied to designing dry dual-clutch transmissions for machines of various purposes.

Multi-Objective Optimization Of Gear Ratios In Two-Speed Dual Clutch Transmissions For Electric Vehicles

The rational matching and optimized design of the gear ratios for the transmission system of an electric vehicle (EV) are of great importance for improving economic and dynamic performances. This paper sets a pure electric vehicle (PEV) as the research object. First, the four common driving cycles considering the urban and suburban areas are selected and analysed which are applied for designing the gear ratios. Second, the parameter matching of the basic indicators of the EV performance and the selection of gear ratios are explored according to the analysis of the four selected driving cycles. Furthermore, gear ratios are set as the variables and the ant colony optimization (ACO) algorithm is applied to optimize the gear ratios by setting the sum of the power demand of the selected common driving cycles, the sum of the average motor efficiency of the chosen driving cycles, and the acceleration time as the objective function in order to optimize the vehicle performances. A two speed dual clutch EV model is constructed in MATLAB/Simulink for verification of the results. The simulation results demonstrate the effectiveness of the optimisation in comparison with the previous gear ratios, where both economic and dynamic performance improvements are evident.

Modelling of a magneto-rheological fluid dual clutch with BP neural network

Modelling of a magneto-rheological fluid dual clutch with BP neural network

Intelligent Control of Starting Process for Dual Clutch Transmissions for Friction Coefficient Self-adaptation

Intelligent Control of Starting Process for Dual Clutch Transmissions for Friction Coefficient Self-adaptation

Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer

Adaptive Pressure Control of the Clutch Hydraulic Actuator in Wet Dual Clutch Transmission Based on T-S Fuzzy Model and Extended State Observer

Modelling of a magneto-rheological fluid dual clutch with BP neural network

Modelling of a magneto-rheological fluid dual clutch with BP neural network

Target State Optimization: Drivability Improvement for Vehicles with Dual Clutch Transmissions

Vehicles with dual clutch transmissions (DCT) are well known for their comfortable drivability since gear shifts can be performed jerklessly. The ability of blending the torque during gear shifts from one clutch to the other, making the type of automated transmission a perfect alternative to torque converters, which also comes with a higher efficiency. Nevertheless, DCT also have some drawbacks. The actuation of two clutches requires an immense control effort, which is handled in the implementation of a wide range of software functions on the transmission control unit (TCU). These usually contain control parameters, which makes the behavior adaptable to different vehicle and engine platforms. The adaption of these parameters is called calibration, which is usually an iterative time-consuming process. The calibration of the embedded software solutions in control units is a widely known problem in the automotive industry. The calibration of any vehicle subsystem (e.g., engine, transmission, suspension, driver assistance systems for autonomous driving, etc.) requires costly test trips in different ambient conditions. To reduce the calibration effort and the accompanying use of professionals, several approaches to automize the calibration process are proposed. Due to the fact that a solution is desired which can optimize different calibration problems, a generic metaheuristic approach is aimed. Regardless, the scope of the current research is the optimization of the launch behavior for vehicles equipped with DCT since, particularly at low speeds, the transmission behavior must meet the intention of the driver (drivers tend to be more perceptive at low speeds). To clarify the characteristics of the launch, several test subject studies are performed. The influence factors, such as engine sound, maximal acceleration, acceleration build-up (mean jerk), and the reaction time, are taken into account. Their influence on the evaluation of launch with relation to the criteria of sportiness, comfort, and jerkiness, are examined based on the evaluation of the test subject studies. According to the results of the study, reference values for the optimization of the launch behavior are derived. The research contains a study of existing approaches for optimizing driving behavior with metaheuristics (e.g., genetic algorithms, reinforcement learning, etc.). Since the existing approaches have different drawbacks (in scope of the optimization problem) a new approach is proposed, which outperforms existing ones. The approach itself is a hybrid solution of reinforcement learning (RL) and supervised learning (SL) and is applied in a software in the loop environment, and in a test vehicle.

Hierarchical control of starting process for wet dual clutch transmission based on direct-drive pump-controlled hydraulic actuator

Hierarchical control of starting process for wet dual clutch transmission based on direct-drive pump-controlled hydraulic actuator

Optimal Clutch Torque Prediction for Shifting Process of Dual Clutch Transmission Based on Support Vector Regression

Optimal Clutch Torque Prediction for Shifting Process of Dual Clutch Transmission Based on Support Vector Regression

Research on intelligent launching control of dual clutch transmissions based on adaptive neural fuzzy inference system

Research on intelligent launching control of dual clutch transmissions based on adaptive neural fuzzy inference system