Torque Phase Shift Control Based on Clutch Torque Estimation

2013 ◽  
Author(s):  
Diana Yanakiev ◽  
Yuji Fujii ◽  
Eric Tseng ◽  
Gregory M. Pietron ◽  
Joseph Kucharski ◽  
...  
Keyword(s):  
Closed Loop ◽  
Automatic Transmission ◽  
Time Estimation ◽  
Transfer Phase ◽  
Shift Method ◽  
Shift Control ◽  
Input And Output ◽  
Torque Estimation ◽  
Real Time Estimation ◽  
Clutch Torque

An automatic transmission shift method is presented, in which the torque transfer phase is controlled in closed loop. This is made possible by real-time estimation of the torque transmitted by the off-going and on-coming clutches participating in the shift. Each clutch torque is determined based on measured or estimated input and output shaft torques and accelerations. To illustrate an application of the method, traditional friction elements are used to emulate one-way-clutch function during a power-on upshift.

Research of Gear Shift Control Technology for a New 8-Step Speed Automatic Transmission

2013 ◽  
Vol 455 ◽  
pp. 376-382 ◽  
Author(s):  
Yang Liu ◽  
Shu Han Wang ◽  
Xi Lu ◽  
Ting Bin Song ◽  
Wen Shu Wei ◽  
...  
Keyword(s):  
Control Algorithm ◽  
Automatic Transmission ◽  
Estimation Method ◽  
Engineering Application ◽  
Shift Control ◽  
Torque Estimation ◽  
Set Up ◽  
Control Principle ◽  
Shift Clutch ◽  
The Ideal

For the development research for a new 8 step speed automatic transmission, a simplified dynamic model for this transmission was established. Aimed at four basic shift types, the ideal characteristics of shift clutch and engine control were set up. By using torque estimation method, PI slip control algorithm and engine coordinated control principle, the control model were developed for two main shift phases which are torque phase and inertia phase. The test on the rig and vehicle verified the accuracy and feasibility of this shift control strategy. The development model and algorithm have a high value for engineering application.

A New Real-time Method for Sailboat Performance Estimation Based on Leeway Modeling

2013 ◽  
Author(s):  
Ronan Douguet ◽  
Jean-Philippe Diguet ◽  
Johann Laurent ◽  
Yann Riou
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Time Estimation ◽  
Real Data ◽  
Performance Estimation ◽  
Sensor Data ◽  
Ocean Current ◽  
Loop Model ◽  
Specific Step ◽  
Real Time Estimation

This paper presents new methods for real time estimation of leeway and ocean current, which are based on boat displacements. We propose two solutions that rely on several types of Kalman filters. The first one uses the empirical leeway definition and allows finding the key parameter of this formula. The solution works properly if the error of the formula of leeway remains limited. The second solution takes advantage of an additional sensor and we compare three methods to linearize boat displacements, which are based on a closed-loop model including cascaded filters. These methods are tested on simulation and on real data collected with a maxi multihull. The results first validate the use of a DVL sensor for leeway estimation but also show that it requires the implementation of a complex and specific step of signal processing. Secondly our study demonstrates the relevancy of the closed-loop approach and shows that a solution, based on UKF filters, provides a relevant method to cope with accuracy and stability in case of sensor data outage.

A machine for real-time estimation of the tribological characteristics of materials

2020 ◽  
Vol 86 (4) ◽  
pp. 61-65
Author(s):  
M. V. Abramchuk ◽  
R. V. Pechenko ◽  
K. A. Nuzhdin ◽  
V. M. Musalimov
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Tribological Characteristics ◽  
Continuous Processing ◽  
Friction Machine ◽  
Dynamic Friction Coefficient ◽  
Displacement Sensors ◽  
Frictional Interaction ◽  
Real Time Estimation ◽  
Automated Quality Control

A reciprocating friction machine Tribal-T intended for automated quality control of the rubbing surfaces of tribopairs is described. The distinctive feature of the machine consists in implementation of the forced relative motion due to the frictional interaction of the rubbing surfaces fixed on the drive and conjugate platforms. Continuous processing of the signals from displacement sensors is carried out under conditions of continuous recording of mutual displacements of loaded tribopairs using classical approaches of the theory of automatic control to identify the tribological characteristics. The machine provides consistent visual real time monitoring of the parameters. The MATLAB based computer technologies are actively used in data processing. The calculated tribological characteristics of materials, i.e., the dynamic friction coefficient, damping coefficient and measure of the surface roughness, are presented. The tests revealed that a Tribal-T reciprocating friction machine is effective for real-time study of the aforementioned tribological characteristics of materials and can be used for monitoring of the condition of tribo-nodes of machines and mechanisms.

Onboard Real-time Estimation of Mean Orbital Elements with Atmospheric Drag

2013 ◽  
Vol 39 (10) ◽  
pp. 1722
Author(s):  
Zhao-Wei SUN ◽  
Wei-Chao ZHONG ◽  
Shi-Jie ZHANG ◽  
Jian ZHANG
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Atmospheric Drag ◽  
Orbital Elements ◽  
Real Time Estimation

Soft sensor for real-time estimation of tablet potency in continuous direct compression manufacturing operation

2021 ◽  
Vol 602 ◽  
pp. 120624
Author(s):  
Reza Kamyar ◽  
David Lauri Pla ◽  
Anas Husain ◽  
Giuseppe Cogoni ◽  
Zilong Wang
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Soft Sensor ◽  
Direct Compression ◽  
Real Time Estimation

scholarly journals A Fusion Algorithm for Estimating Time-Independent/-Dependent Parameters and States

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4068
Author(s):  
Zheshuo Zhang ◽  
Jie Zhang ◽  
Jiawen Dai ◽  
Bangji Zhang ◽  
Hengmin Qi
Keyword(s):  
Unscented Kalman Filter ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Fusion Algorithm ◽  
State Variable ◽  
Current Estimation ◽  
Real Time Estimation ◽  
And Control ◽  
Independent Parameters

Vehicle parameters are essential for dynamic analysis and control systems. One problem of the current estimation algorithm for vehicles’ parameters is that: real-time estimation methods only identify parts of vehicle parameters, whereas other parameters such as suspension damping coefficients and suspension and tire stiffnesses are assumed to be known in advance by means of an inertial parameter measurement device (IPMD). In this study, a fusion algorithm is proposed for identifying comprehensive vehicle parameters without the help of an IPMD, and vehicle parameters are divided into time-independent parameters (TIPs) and time-dependent parameters (TDPs) based on whether they change over time. TIPs are identified by a hybrid-mass state-variable (HMSV). A dual unscented Kalman filter (DUKF) is applied to update both TDPs and online states. The experiment is conducted on a real two-axle vehicle and the test data are used to estimate both TIPs and TDPs to validate the accuracy of the proposed algorithm. Numerical simulations are performed to further investigate the algorithm’s performance in terms of sprung mass variation, model error because of linearization and various road conditions. The results from both the experiment and simulation show that the proposed algorithm can estimate TIPs as well as update TDPs and online states with high accuracy and quick convergence, and no requirement of road information.

scholarly journals Real-Time Estimation of Microgrid Inertia and Damping Constant

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ujjwol Tamrakar ◽  
David A. Copp ◽  
Tu Nguyen ◽  
Timothy M. Hansen ◽  
Reinaldo Tonkoski
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Real Time Estimation
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