Automatic Transmission System Research Articles

A pitting fault diagnosis method for planetary gear in automatic transmission based on multiple advantageous sub-band signal fusion

Abstract Localized pitting in planetary gears is a critical fault in the automatic transmission (AT) systems of heavy-duty vehicles, and identifying this fault is an important aspect of vehicle maintenance. The single sensor often fails to capture comprehensive fault information from the housing of the AT. To fully capture fault characteristics from multi-sensor data and improve the accuracy of intelligent fault diagnosis, this paper proposes a pitting fault diagnosis method based on the fusion of multiple advantageous sub-band signals. Initially, the proposed method employs variational mode decomposition based on K-optimization to demodulate the raw fault signals acquired by various sensors. Subsequently, the advantageous sub-band signals, which contain the pitting fault information, are selected by integrating two indices: Variance Accounted For (VAF) and Spectral Entropy (H(F)). These selected sub-band signals are then fused using a data fusion method based on the dissimilarity measure. Finally, a 1D-AlexNet model is constructed to diagnose the fused signals. The validity and superiority of this method are confirmed through a pitting fault injection experiment in a AT test rig. This paper also compares other diagnosis methods to further demonstrate the superiority of the proposed method.

Intelligent gear decision method for vehicle automatic transmission system based on data mining

The gear decision logic of automatic transmission directly affects the vehicle's dynamic, fuel economic, and comfort performance. This study employs data mining techniques to address the issues of low adaptability and low recognition rate in the intelligent gear decision of vehicle automatic transmission systems. The research further proposes the utilization of Kalman filter, Hidden Markov Models, and Long Short-Term Memory networks for condition feature recognition and time series classification. Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. Combining driver intent and driving environment, an intelligent gear decision method is formulated. The results indicate that, during a 430 s driving segment, the intelligent gear decision method consumes only 464 mL of fuel, closely resembling the economic strategy's 457 mL, with a gear shift frequency of 53, significantly better than the 79 shifts in the economic strategy. Moreover, the error rate for slope condition recognition is only 0.062 %. In a 200 s coupled condition, the intelligent gear decision results in fuel consumption of 207 mL, approximating the actual vehicle's 219 mL, while power-shifting consumes 316 mL, and economic shifting only 202mL. This study not only improves the accuracy of gear decisions but also effectively enhances vehicle operational efficiency, providing valuable insights for future automatic transmission systems with significant practical value.

Switching to a 100% remote follow-up of implantable cardiac electronic devices: Organizational model and results of a single center experience.

During the SARS-CoV-2 COVID-19 pandemic, the global health system needed to review important processes involved in daily routines such as outpatient activities within the hospital, including follow-up visits of implantable cardiac electronic devices (CIEDs) carried out in office. The aim of this study is to describe our 3.5 years of real-world experience of a full remote CIED follow-up, evaluate the success rate of remote transmissions, and verify the adopted organizational model. From April 2020 to November 2023, all patients with an activated and well-functioning remote monitoring (RM) system and automatic algorithms, like autocapture and autosensing, underwent exclusive RM follow-up. Unscheduled in-office visits were only prompted by remote yellow or red alerts. Patients were divided into two groups, based on available technology: Manual Transmission System (MTS) and Automatic Transmission System (ATS). The ATS group, in addition to ensuring a daily transmission of any yellow or red alerts, was checked at least every 15 days to ensure a valid connection. An automatic transmission was scheduled once a year, irrespective of alerts occurred. The MTS group provided a manual transmission every 6 months. One thousand nine hundred thirty-seven consecutive patients were included in the study. By the end of November 2023, a total of 1409 patients (1192 in the ATS and 217 in the MTS group) were still actively followed by our remote clinic (384 expired, 137 dismissed, 7 transferred). The overall success rate of transmissions with the adopted organizational model was 96.6% in the ATS group (connection index) and 87% in the MTS group. Conventional in-hospital follow-up visits decreased by 44%. Total clinic working time, resulting from the sum of the time spent during in-hospital and remote follow-up, after an initial increase, was progressively reduced to the actual -25%. Mortality rate for any cause was 7.5% per year in remote follow-up patients and 8.3% (p=NS) in in-office patients. In the ATS group, no device malfunctions were notified to our remote clinic, before we had already realized it through appropriate alerts. The available technology makes moving to a 100% remote clinic possible, without overwhelming clinic workflow, safely. Adopting an appropriate organizational model, it is possible to maintain high transmission success rates. The automatic transmissions allow a more frequent control of patients with CIED.

Удосконалення методу оцінки програмного забезпечення контролю параметрів транспортних засобів

The purpose of the conducted research is to improve the method of evaluating the performance of the vehicle parameter control software. It is stated that a new technique for road transport in the field of monitoring its working condition is the creation of information systems for organizational and functional support of rolling stock operation processes with the help of information integration, namely the stages of the life cycle of rolling stock and systems for its technical control and diagnostics. It is shown that nowadays in road transport the basis of life cycle information support can be CALS or IPV/CALS/PLM - technologies (continuous support of the life cycle of vehicles), which are sometimes called product information support systems and are a part of intelligent transport systems. The analysis and clarification of the structure of the intelligent vehicle monitoring system was carried out on the example of the assessment of its environmental safety and its engine parameters. In the work, it is also planned to obtain experimental data from vehicle, the results of processing of which will allow to prove the existence of a real possibility of using the diagnostic complex on a modern automatic transmission system. It should be noted that the system for monitoring environmental safety indicators of vehicle, which is proposed by the authors, also contains in its composition the subsystem of intelligent processing of primary information, which can be used precisely in the role of "intelligent monitoring system". The data obtained and analyzed in the work indicate the need to also improve the efficiency of the neutralization of harmful substances in the engine warm-up mode, which can be implemented by reducing the engine warm-up time and more effective control of the injection/ignition process in transient modes, as well as by introducing an improvement algorithm of the control subsystem composition of the mixture precisely with feedback. The main diagnostic parameters of the vehicle engine during the start-up and warm-up processes, which affect the composition of harmful substances in the exhaust gases, were obtained experimentally. The proposed scheme for monitoring pollution of the roadside environment by traffic flows in the city.

Fault Identification of Direct-Shift Gearbox Using Variational Mode Decomposition and Convolutional Neural Network

The direct-shift gearbox is widely used in many applications, such as automotive and aerospace, due to its large transmission ratio and high transmission efficiency. Rough and heavy-duty working conditions induce various faults, such as scratches, fatigue cracks, pitting, and missing teeth due to breakage. These defects may lead to the failure of one or more components attached to an automatic transmission system. A fault identification scheme for the direct-shift gearbox has been developed, making use of variational mode decomposition (VMD) and convolutional neural network (CNN). The acquired raw signal from the gearbox under different health conditions (healthy, pitting, and chipping) is decomposed into different modes using VMD. The prominent mode is selected based on kurtosis, which is utilized to obtain scalograms. An image matrix is formed utilizing scalograms. Such matrices from different scalograms are divided into training and testing matrices. The training matrices train the CNN model, whereas the testing matrices validate the efficacy of the built CNN model. The proposed scheme identifies faults with 100% accuracy. The proposed scheme has also been compared with other neural networks. These results suggest that the proposed scheme outperforms other networks.

STUDI KASUS PERHITUNGAN TEGANGAN PADA FLAT BELT DALAM APLIKASI MESIN IHR

The Continuously Variable Transmission (CVT) automatic transmission system is a power transmission component widely used in various industrial sectors such as manufacturing, paper, automotive, and electric power. The decision to use this transmission is made due to its ease of maintenance, affordability, and its ability to operate within various power and speed ranges. Key components of the CVT automatic transmission system include flat belts, pulleys, rollers, CVT springs, CVT clutch linings, and clutch clutches. Calculation analysis will be conducted to determine the maximum stress of the flat belt, identify the material of the flat belt, and calculate the lifespan of the flat belt using the IHR machine. The results of the calculation show that the tight side stress is 383.3639 N, the loose side stress is 64.867 N, and the belt material stress is 3.1 N/mm2. These optimal stress and material stress values are deemed suitable for use.

Comparison of Standard and Racing Roller Weight Variations on CVT on the Power and Torque of the Honda Beat 110cc

This automatic motorbike uses an automatic transmission system called CVT (Contynously Variable Transmission). CVT is a system that automatically changes speed according to engine speed. This machine does not use transmission gears, but instead uses two pulleys (front and rear) which are connected by a belt (v-belt. The advantege of a CVt automatic transmission is that it can provide speed changes in torque from the engine to the rear whells automatically. This research aims to determine the effect of roller weight on the power and engine torque of a 110 cc two wheeled vehicle. The background of this research is to determine the power and torque of motorbikes for each roller weight studied and to draw conclusions about better use of rollers weight. This research uses experimental research methods, the materials used are standard 12gr,11gr,10gr,9gr,8gr rollers, as a comparison and 110cc injection beat motorbikes. The toll used in this research is a dynamometer. This tool shows directly the maximum power results at a certain rpm. Changes in the weight of the Honda Beat 110cc CVT roller affect the power produced by the engine. Changes in roller weight can affect the size of the engine’s power and torque. This in proven by data showing changes in engine power and torque during each test. Therefore, it is hoped that the result of this test can be used as a reference for improving engine peformance in vehicles.

Dynamic analysis of planetary gear system for automatic transmission

Abstract Dynamic analysis can provide a theoretical basis for controlling vibration and noise in gear systems, as well as calculating strength under dynamic conditions. This paper takes 6HP26 automatic transmission as the research object, takes the fifth-gear transmission as an example, adopts the centralized mass method to establish its translation-torsion coupling dynamic model, and analyzes the displacement response, torsional linear acceleration time-domain response and spectrogram of each component. This provides a reference for reducing vibration and noise in the system.

Robust Position Control for an Electrical Automatic Transmission under Gear-Shifting Link Friction

The automotive industry is evolving, with software becoming a vital part of vehicles. Conventional automakers are shifting to software-centric entities, embracing over-the-air (OTA) updates and service-centric models. To move software-driven vehicles, the vehicle must also be electrified. Several automobile manufacturers are electrifying vehicle parts, and recently, a gear shift selector for automatic transmissions was adapted from mechanical to electronic. However, as conventional mechanical systems are modified to electrical systems, problems such as shift delay and accuracy emerge. This study addresses these problems that emerge in the electronic system type of automatic transmission, including a gear shift selector developed to electrify automobiles. Accordingly, we first analyze the structure of automatic transmission systems, then define the operation sequence. Next, a novel position control algorithm based on a disturbance observer is proposed to reduce shift delay and increase accuracy. The proposed algorithm operates harmoniously with the vehicle control unit (VCU). To verify the proposed algorithm, a hardware-in-the-loop simulation (HILS) was developed to experiment with vehicle shifting using a commercial electronic gear shift selector. Moreover, the proposed control algorithm for gear shifting in an automatic transmission was analyzed using experimental results obtained by assuming a specific driving situation in the HILS.

Noise analysis and optimization of the gear transmission system for two-speed automatic transmission of pure electric vehicles

Abstract. In this study, the noise of the gear transmission system for two-speed automatic transmission (2EAT) of pure electric vehicles was analyzed and optimized. Firstly, through vehicle noise tests, poor working conditions and noise contribution of each gear pair were determined with the order analysis method. Secondly, a dynamics calculation model and a simulation model of the gear transmission system were established and the poor meshing state of the main reducer gear pair under specific conditions was determined as the main cause of noise. Finally, a genetic algorithm combined the weight method was used for gear modification. After gear modifications, the fluctuation range of transmission error was reduced and the contact condition of the tooth surface was significantly improved.

THE EFFECT OF V-BELT SIZE AND GROOVE ANGLE VARIATION ON THE SURFACE OF THE CVT CLUTCH DISK ON THE POWER AND TORQUE TRANSMISSION OF 125CC MOTORCYCLE

Continuously Variable Transmission (CVT) is an automatic transmission system with gear ratio shifts following engine speed controlled by the primary and secondary pulleys, as well as the V-belt that connects the two pulleys. The disadvantage of the CVT transmission system is that it often loses grip on the CVT clutch lining and the V-belt at low and high rotation so that research needs to be done so that the power from the engine to the wheels can be maximized. This study used an experimental method by changing the variation in the size of the V-belt and the groove angle on the clutch pads to find the best size for a 125 CC motorbike. The results showed that to get maximum results it is recommended to use a V-belt 803 x 19.0 mm with a CVT lining of 30° producing the highest power and a V-belt 840 x 21.8 mm with a CVT lining of 90° producing the highest torque

Follow-up of implantable cardiac electronic devices during the Covid-19 pandemic: organizational model and results of a single center experience

Abstract Funding Acknowledgements Type of funding sources: None. Introduction During the SARS-CoV-2 COVID-19 pandemic, the global health system has had to review important processes involved in daily routines such as outpatient activities within the hospital, including follow-up visits of implantable cardiac electronic devices (CIEDs), pacemakers (PMs) and implantable defibrillators (ICDs) carried out in office. The aim of this study was to prospectively evaluate the success rate of remote transmissions of all devices followed by the CIED control clinic and verify the adopted organizational models. Methods All patients with remote monitoring system were considered in the study if automatic algorithm such as autocapture and autosensing were activated and well-functioning. Between January 2021 and November 2022, they were completely followed by remote monitoring and called for unscheduled in-office visit only because of remote yellow or red alarms. Patients were divided into two groups: Manual Transmission System (MTS) and Automatic Transmission System (ATS), based on the available technology. Organizational models shown in figures 1-2, were followed for the two groups. The technology of the ATS group, in addition to ensuring a daily transmission of any yellow or red alarms, allowed a control of missed communication at least every 14 days. The MTS group provided a manual transmission every 6 months. The ATS group was controlled at least once in the year, even if no alarms occurred. Results At the end of 2022 a total of 1193 patients were followed remotely by our center. Of these, 238 from the MTS group and 955 from the ATS group. 3314 remote transmission required medical intervention, which generated 182 unscheduled outpatient visits, mainly due to lack of transmission for prolonged periods, failure of the autocapture test and newly onset atrial fibrillation. 3496 transmissions were generated and 120 transmissions were missed; the overall success rate of transmissions with the organizational model adopted was 96.6% (connectivity index). On average, the monthly rate of unconnected manual devices was 5.1% while 3.5% for automatic devices. 2-year mortality was 12.7%. Conclusions By adopting an appropriate organizational model, it is possible to maintain high transmission success rates. The available technology allows you to change hospital outpatient habits in the cardiology field for CIED checks and move to a virtual clinic safely. The automatic transmission technology allows a more frequent control of patients with CIED, the impact on the patients' health must be assessed.

Auto-Tracking Wireless Power Transfer System With Focused-Beam Phased Array

This article used image recognition and beam forming technology to build a phased array with target tracking and transmitting the microwaves with a focused beam. The coordinate position of the target is obtained from the image recognition module and converted into phase information for the phased array. This system was constructed by a 1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> 4 5.764-GHz phased array with four 4-bit phase shifters. The phase shifters created a focused beam, which requires not only the target’s direction angle but also the transmission distance. The target position as well as direction and distance information were gathered using image recognition. The tracking beam method was evaluated by simulation and actual measurement. The results showed that the focused beam can always be formed in real time to track the target. The transfer efficiency of the focused beam was improved higher than that of uniform phase beam within a distance of 50 cm. The automatic tracking power transmission system has a response time of about 100 ms.

Design of a mechanical automatic transmission system for automobiles based on torsional vibration damping

Abstract In order to reduce the vibration damage of the engine and improve the automatic transmission adjustment performance of the automobile, an automatic transmission system based on torsional damping is constructed in this paper to optimize the hardware function of the shift speed. The torsional damper is used as the core control element to reciprocate the automotive mechanical automatic transmission system, and the calculation method of torsional vibration analysis of the crankshaft shaft system is used to determine the indexes of rotational inertia, stiffness, and damping parameters of torsional vibration. The damping coefficient values are set near the equilibrium point, and the loss factor of the automatic transmission system is signal processed to obtain the best damping effect. Using the intrinsic frequency as the central processing unit of the automatic transmission system, the differential equation is used to calculate the excitation torque vector of each cylinder of the engine, and the characteristic module of the automatic transmission system is developed. The tests showed that the cylinder burst pressure of the automatic transmission system with the torsional damper reached a maximum of 67.9 pressure at 4800 amp. The crankshaft front-end torsional angle of the 4th-order main harmonic excitation reached a maximum of 0.57 degrees, which exceeded the engineering allowance of 0.2 degrees and reduced the automatic shift shock by about 28.36%. It indicates that the torsional damper can improve the control performance of the automatic transmission system, which is conducive to enhancing the stability and self-adaptive capability of the transmission adjustment.

Design of automotive mechanical automatic transmission system based on torsional vibration reduction

Automatic transmission system is the core part of vehicle transmission processing, which can improve driving safety. In order to improve the shift effect of automotive automatic mechanical transmission and narrow the gap between the vehicle speed and the expected speed, an automotive automatic mechanical transmission system based on torsional damping was designed in the experiment. On the basis of hardware composed of different modules and fuzzy control algorithm, the system realizes the software design of vehicle automatic mechanical transmission system. The experimental results show that when the system is applied in practice, the gear selection time of the vehicle is between 0.2 s-0.3 s, and the gear shift time is between 0.3 s-0.4 s. The gap between the vehicle speed and the expected speed, and between the vehicle speed and the expected speed is small. The practical application effect is good.

Effect of Butanol-Gasoline Blend Toward Performance Matic-Transmission Applied in Single Cylinder Capacity Engine

The availability of fuel oil is decreasing while the level of consumption is increasing. This encourages the need for the development of alternative energy to minimize the crisis. This study investigates the characteristics of fuel and automatic transmission combustion engines. The fuel used is butanol variations B7, B12 and B18 (7%, 12%, and 18%) and pertalite (RON-90). The gasoline engine used has a capacity of 110 cc with a compression ratio of 9.5:1, an automatic transmission system, and air conditioning. The performance test equipment used is the Dynotest-chassis type 50L-BRT. Fuel variations are applied to an engine performance test by using engine speeds of 3000-9000 rpm. The results showed that the use of 18% butanol increased the output power and thermal efficiency by 8.3 kW and 923.95 kPa at 8000 rpm. torque and MEP (average effective pressure) increased by 8 N.m and 923.95 kPa at 5000 rpm. Meanwhile, SFC (specific fuel consumption) decreased by 0.35 kg/kWh at 8000 rpm.

Intelligent Gear Decision Method for Automatic Vehicles Based on Data Mining Under Uphill Conditions

Existing gear decision methods are affected by the limiting factors of deviation of numerical models as well as the subjectivity of the designer, which results in poor adaptability to the driving intentions and driving environments. Excellent drivers are able to choose the appropriate gear to satisfy their driving intentions and respond to changes in driving environments when driving manual transmission vehicles. Therefore, an intelligent gear decision method and design methodology of vehicle automatic transmission system that adapts to different driving intentions and complex driving environments are constructed from the massive driving data of excellent drivers by using data mining method. Excellent drivers are employed to drive vehicles with manual transmission to obtain a large amount of driving data. Subsequently, data preprocessing, data cleaning, and outlier removal are performed on the collected driving data to extract the shift boundary points of each gear aiming at constructing the shift rule surface of each gear. Using the uphill condition as an example, a data-mining-based shift control strategy is established, and the comparison results verify that the proposed gear decision design method can mine the shift strategy of excellent drivers from massive driving data, and the constructed strategy can better adapt to the driver’s intention while obtaining better fuel economy and avoiding unreasonable gearshifts compared with the automatic transmission’s default strategy.

Optimal Control of the Logistics Automation Transmission System Based on Partial Differential Equation

In this paper, the finite difference scheme of the spatiotemporal fractional convection-diffusion equation is established, and its stability and convergence are proved. Furthermore, this discrete technique is extended to solve nonlinear spatiotemporal fractional convection-diffusion equations. By using the Krylov subspace method to solve the discrete system, the numerical solution of the spatiotemporal fractional convection-diffusion equation can be obtained quickly. In this paper, an efficient optimal control algorithm is proposed to solve the free control problem of a class of nonlinear time-delay systems. We obtained the optimal control law of the system through the Bellman optimality principle, obtained the asymptotic stability criterion of the system in the form of LMI under the optimal control input by using the Lyapunov stability theory, and discussed the effect of the delay parameter on the system stability. Using the principle of intelligent neural network approximation function, the evaluation neural network and the execution neural network are used to approximate the optimal performance index function and optimal control input, respectively, the optimal control strategy of the system is obtained, and the convergence of the weight estimation error is proved to be optimal. On the basis of optimal state adjustment, the optimal tracking control problem is further solved. Numerical example results verify the effectiveness of the proposed method in terms of stability analysis, optimal state control, and optimal tracking control for the nonlinear time-delay system proposed in this paper. We calculate the parameters of the conveyor and select a reasonable transmission and sorting mechanism to realize the speed regulation of the driving motor of each mechanism. Through the work of each part, the design scheme of the automatic transmission system is formed, and the reliability, practicability, and economy of the system are guaranteed.

Logic design method and optimization of hydraulic system for heavy-duty automatic transmission

In this paper, the shifting control hydraulic system of the heavy-duty automatic transmission was designed, aiming to unify and standardize design methods. The said system was designed according to the binary logic characteristics of hydraulic components. In addition, to meet the torque transmission requirements and reduce the energy consumption, both the oil pressure supply and flow-regulating system were designed. Mathematical and simulation models of the hydraulic system were established to analyze its performance. Finally, the genetic algorithm was used to optimize the system (within the AMESim environment); the results have shown that the main pressure of each gear was controlled in a reasonable range, and both the pressure of shift clutch and the pressure response time were reduced. In addition, the power loss of the hydraulic system was significantly improved, which improved the practical performance of the overall hydraulic system.

Towards an effective application of parameter estimation and uncertainty analysis to mathematical groundwater models

Groundwater models serve as support tools to among others: assess water resources, evaluate management strategies, design remediation systems and optimize monitoring networks. Thus, the assimilation of information from observations into models is crucial to improve forecasts and reduce uncertainty of their results. As more information is collected routinely due to the use of automatic sensors, data loggers and real time transmission systems; groundwater modelers are becoming increasingly aware of the importance of using sophisticated tools to perform model calibration in combination with sensitivity and uncertainty analysis. Despite their usefulness, available approaches to perform this kind of analyses still present some challenges such as non-unique solution for the parameter estimation problem, high computational burden and a need of a deep understanding of the theoretical basis for the correct interpretation and use of their results, in particular the ones related to uncertainty analysis. We present a brief derivation of the main equations that serve as basis for this kind of analysis. We demonstrate how to use them to estimate parameters, assess the sensitivity and quantify the uncertainty of the model results using an example inspired by a real world setting. We analyze some of the main pitfalls that can occur when performing such kind of analyses and comment on practical approaches to overcome them. We also demonstrate that including groundwater flow estimations, although helpful in constraining the solution of the inverse problem as shown previously, may be difficult to apply in practice and, in some cases, may not provide enough information to significantly constrain the set of potential solutions. Therefore, this article can serve as a practitioner-oriented introduction for the application of parameter estimation and uncertainty analysis to groundwater models.