scholarly journals Vehicle diagnostic technology

2022 ◽  
Vol 14 (2) ◽  
pp. 10-17
Author(s):  
Volodymyr Volkov ◽  
◽  
Volodymyr Kuzhel ◽  
Tetiana Volkova ◽  
Ganna Pliekhova ◽  
...  
Keyword(s):  
Control System ◽  
Fuel Consumption ◽  
Data Transfer ◽  
Automatic Transmission ◽  
Real Data ◽  
Electrical Equipment ◽  
Diagnostic Process ◽  
Current Time ◽  
The Individual ◽  
Error Memory

In the article, using the example of a mechatronic control system for the engine and transmission of vehicles (automobiles), the features of the technology of their diagnosis are shown. In an electronic transmission control system, the object of regulation is mainly an automatic transmission. Also, the laws of control (programs) of gear shifting in an automatic transmission ensure the optimal transfer of engine energy to the wheels of the vehicle (TC), taking into account the required traction and speed properties and fuel economy. At the same time, the programs for achieving optimal traction-speed properties and minimum fuel consumption differ from each other, since the simultaneous achievement of these goals is not always possible. Therefore, depending on the driving conditions and the desire of the driver, using a special switch, you can select the "economy" program to reduce fuel consumption, the "power" program - to improve traction and speed properties, or the "manual" program to switch gears by the driver. In turn, self-diagnostic capabilities include: system identification and electronic control units (ECU) (ECU); recognition, storage and reading of information about static and single malfunctions; reading current real data, including environmental conditions and specifications; modeling of system functions; programming of system parameters. The individual programs for the test block are stored in the plug-in modules, while the correction and data transfer in the system is carried out via the data interface. Note also that the diagnostic process begins with the initialization of the systems - their detection in the electrical equipment of the vehicle. Upon successful initialization, it is possible to: read the error memory; erase the error memory; view the data of the next detected system or exit to the main menu; change the readings of the selected category; correct the current time; correct the current date and perform a number of additional functions.

scholarly journals Supervised dimensionality reduction for big data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joshua T. Vogelstein ◽  
Eric W. Bridgeford ◽  
Minh Tang ◽  
Da Zheng ◽  
Christopher Douville ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Data Science ◽  
Real Data ◽  
Low Rank ◽  
Conditional Moment ◽  
Desktop Computer ◽  
Reduction Techniques ◽  
Reduction Methods ◽  
The Individual ◽  
Low Dimensional

AbstractTo solve key biomedical problems, experimentalists now routinely measure millions or billions of features (dimensions) per sample, with the hope that data science techniques will be able to build accurate data-driven inferences. Because sample sizes are typically orders of magnitude smaller than the dimensionality of these data, valid inferences require finding a low-dimensional representation that preserves the discriminating information (e.g., whether the individual suffers from a particular disease). There is a lack of interpretable supervised dimensionality reduction methods that scale to millions of dimensions with strong statistical theoretical guarantees. We introduce an approach to extending principal components analysis by incorporating class-conditional moment estimates into the low-dimensional projection. The simplest version, Linear Optimal Low-rank projection, incorporates the class-conditional means. We prove, and substantiate with both synthetic and real data benchmarks, that Linear Optimal Low-Rank Projection and its generalizations lead to improved data representations for subsequent classification, while maintaining computational efficiency and scalability. Using multiple brain imaging datasets consisting of more than 150 million features, and several genomics datasets with more than 500,000 features, Linear Optimal Low-Rank Projection outperforms other scalable linear dimensionality reduction techniques in terms of accuracy, while only requiring a few minutes on a standard desktop computer.

scholarly journals Controlling response dependence in the measurement of change using the Rasch model

2017 ◽  
Vol 27 (12) ◽  
pp. 3709-3725 ◽  
Author(s):  
David Andrich
Keyword(s):  
Rasch Model ◽  
Real Data ◽  
Repeated Measurements ◽  
Measurement Of Change ◽  
Location Parameters ◽  
Response Dependence ◽  
The Individual ◽  
First Time ◽  
The Rasch Model ◽  
Research And Policy

The advantages of using person location estimates from the Rasch model over raw scores for the measurement of change using a common test include the linearization of scores and the automatic handling of statistical properties of repeated measurements. However, the application of the model requires that the responses to the items are statistically independent in the sense that the specific responses to the items on the first time of testing do not affect the responses at a second time. This requirement implies that the responses to the items at both times of assessment are governed only by the invariant location parameters of the items at the two times of testing and the location parameters of each person each time. A specific form of dependence that is pertinent when the same items are used is when the observed response to an item at the second time of testing is affected by the response to the same item at the first time, a form of dependence which has been referred to as response dependence. This paper presents the logic of applying the Rasch model to quantify, control and remove the effect of response dependence in the measurement of change when the same items are used on two occasions. The logic is illustrated with four sets of simulation studies with dichotomous items and with a small example of real data. It is shown that the presence of response dependence can reduce the evidence of change, a reduction which may impact interpretations at the individual, research, and policy levels.

scholarly journals Modeling of Tractor Fuel Consumption

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2300
Author(s):  
Bronisław Andrzej Kolator
Keyword(s):  
Fuel Consumption ◽  
Soil Conditions ◽  
Simulation Studies ◽  
Working Capacity ◽  
Operational Parameters ◽  
System A ◽  
The Individual ◽  
Adjustment System ◽  
Unit Performance ◽  
Efficiency Indicators

In this paper, the energy diagnostic of tractor performance consists in evaluating the energy (fuel consumption per hectare—dm3 ha−1) for a given agricultural operation and in combining it with working capacity, also called productivity (area productivity—ha h−1). One of the methods of solving this problem is the identification of the functioning process of the machine unit. A model of the process of the machine unit performance was developed, considering the operation of the rear linkage system of the implement with the force control adjustment system. In order to analyze the system, a mathematical model of the system function was built: tractor-implement-soil, defining the physical connections and interdependencies between the individual subsystems of the system. Based on this model, a simulation model was developed and implemented in the Matlab/Simulink environment. The Simulink package was used to test the performance of the machine set. The efficiency indicators according to the adopted criteria were calculated in the evaluation block. To evaluate the process, the technical and operational parameters of the tractor, the type and parameters of the tool, and soil properties were taken into account. The results of simulation studies obtained on a validated model are consistent with experimental data from appropriate soil conditions.

Research on Power Regulation Schedule Control System for Turboprop Engine

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Tianqian Xia ◽  
Xianghua Huang
Keyword(s):  
Control System ◽  
Steady State ◽  
Fuel Consumption ◽  
Reference Model ◽  
Sliding Mode ◽  
Speed Control ◽  
Variable Speed ◽  
Turboprop Engine ◽  
Speed Control System ◽  
Variable Speed Control

Abstract A method of variable speed control system for turboprop engine is presented in this paper. Firstly, the steady operation state of turboprop engine is analyzed, and the operating line is figured out in the steady state characteristic diagram, which is the design basis of Engine Thrust Management System (ETMS). Secondly, the reference model sliding mode multivariable control is used to design the control law to follow the speed instructions given by ETMS. Finally, the optimization of the minimum fuel consumption operating curve is realized, and the control system designed is applied to a numerical model of a turboprop engine. The simulation results show that compared with the constant speed control system, the variable speed control system can reduce the specific fuel consumption by 2.37 % on average and 3.1 % in steady state conditions. Furthermore, the method can enable the pilot to manipulate the turboprop aircraft by using only one throttle lever, which can greatly reduce the pilot operation burden.

scholarly journals Sensitivity Analysis of the Battery Model for Model Predictive Control: Implementable to a Plug-In Hybrid Electric Vehicle

2018 ◽  
Vol 9 (4) ◽  
pp. 45 ◽  
Author(s):  
Nicolas Sockeel ◽  
Jian Shi ◽  
Masood Shahverdi ◽  
Michael Mazzola
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Predictive Control ◽  
Hybrid Electric Vehicle ◽  
Control Solution ◽  
Current Time ◽  
Battery Model ◽  
Hybrid Electric

Developing an efficient online predictive modeling system (PMS) is a major issue in the field of electrified vehicles as it can help reduce fuel consumption, greenhouse gasses (GHG) emission, but also the aging of power-train components, such as the battery. For this manuscript, a model predictive control (MPC) has been considered as PMS. This control design has been defined as an optimization problem that uses the projected system behaviors over a finite prediction horizon to determine the optimal control solution for the current time instant. In this manuscript, the MPC controller intents to diminish simultaneously the battery aging and the equivalent fuel consumption. The main contribution of this manuscript is to evaluate numerically the impacts of the vehicle battery model on the MPC optimal control solution when the plug hybrid electric vehicle (PHEV) is in the battery charge sustaining mode. Results show that the higher fidelity model improves the capability of accurately predicting the battery aging.

scholarly journals Smooth Gear Shift Control System of Automatic Transmission Using Estimated Output Shaft Torque.

1995 ◽  
Vol 61 (591) ◽  
pp. 4334-4338
Author(s):  
Toshimichi Minowa ◽  
Hiroshi Kimura ◽  
Junichi Ishii ◽  
Masahiko Ibamoto
Keyword(s):  
Control System ◽  
Automatic Transmission ◽  
Output Shaft ◽  
Gear Shift ◽  
Shift Control ◽  
Shaft Torque

scholarly journals RECORD: Reference-Assisted Genome Assembly for Closely Related Genomes

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Krisztian Buza ◽  
Bartek Wilczynski ◽  
Norbert Dojer
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Real Data ◽  
Reference Sequence ◽  
Individual Genome ◽  
Single Experiment ◽  
Sequencing Technologies ◽  
Sequencing Cost ◽  
The Individual ◽  
Assembly Software

Background. Next-generation sequencing technologies are now producing multiple times the genome size in total reads from a single experiment. This is enough information to reconstruct at least some of the differences between the individual genome studied in the experiment and the reference genome of the species. However, in most typical protocols, this information is disregarded and the reference genome is used.Results. We provide a new approach that allows researchers to reconstruct genomes very closely related to the reference genome (e.g., mutants of the same species) directly from the reads used in the experiment. Our approach applies de novo assembly software to experimental reads and so-called pseudoreads and uses the resulting contigs to generate a modified reference sequence. In this way, it can very quickly, and at no additional sequencing cost, generate new, modified reference sequence that is closer to the actual sequenced genome and has a full coverage. In this paper, we describe our approach and test its implementation called RECORD. We evaluate RECORD on both simulated and real data. We made our software publicly available on sourceforge.Conclusion. Our tests show that on closely related sequences RECORD outperforms more general assisted-assembly software.

Sign in / Sign up

Export Citation Format

Share Document