mode switching
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2022 ◽  
pp. 1-18
Tao Deng ◽  
Zhihan Gan ◽  
Hui Xu ◽  
Changjun Wu ◽  
Yuxiao Zhang ◽  

Abstract Hybrid powertrains with planetary gearset(PG) have been widely used. However, there are few types of powertrains in use, more powertrains have not been found. Based on the principle of organic chemistry, a design and screening method of multi-mode 2-PGs hybrid powertrain is proposed, which is divided into five stages. Firstly, powertrains are expressed in the form of molecules. Secondly, powertrains split into the libraries of PGs and power sources. The power sources can be mutually identified to construct new library. Thirdly, the mode switching rules are defined to screen power source group. Fourthly, two libraries interact with each other to promote the generation of new molecules, namely, new powertrains. And the more modes, the greater the vehicle performance potential. Powertrains are screened with mode richness theory firstly. Finally, taking the comprehensive evaluation of power performance and fuel economy as the optimal standard, powertrains are screened and evaluated twice. Through the method, hybrid powertrains with smooth mode switching, simpler structure, and optimal power and economy can be obtained.

Natee Sirinvaravong ◽  
Mark Heimann ◽  
Steve Liskov ◽  
Gan-Xin Yan

Abstract Background Atrial dissociation (AD) is described as the existence of two simultaneous electrically isolated atrial rhythms. Theoretically, detection of dual atrial rhythms with a sufficiently high rate by pacemaker can lead to automatic mode switching and associated pacemaker syndrome. Such a clinical observation has not been reported before in the literature. Case Summary An 87-year-old female with Ebstein’s anomaly status post tricuspid valve annuloplasty and tricuspid valve replacement and a dual chamber pacemaker presented with congestive heart failure one week after undergoing atrial lead revision. Interrogation of her dual chamber pacemaker revealed two atrial rhythms: sinus or atrial-paced rhythm and electrically isolated atrial tachycardia (AT). Sensing of both atrial rhythms by the pacemaker led to automatic mode switching, which manifested as ventricular paced rhythm with retrograde P waves on electrocardiogram (ECG). Adjusting the atrial lead sensitivity to a level higher than the sensing amplitude of AT restored atrial paced and ventricular sensed rhythm, which resulted in resolution of heart failure symptoms. Discussion Regardless of the cause of AD, there must be electrical insulation between the two rhythms for their independent coexistence in the atria. AD can lead to pacemaker syndrome from automatic mode switching. If the sensing amplitude during sinus rhythm is significantly larger than that of AT, adjusting the atrial lead sensitivity would solve the issue, as in the present case. Otherwise, atrial lead revision, pharmacotherapy or AT ablation should be considered.

Sadra Hemmati ◽  
Rajeshwar Yadav ◽  
Kaushik Surresh ◽  
Darrell Robinette ◽  
Mahdi Shahbakhti

Connected and Automated Vehicles (CAV) technology presents significant opportunities for energy saving in the transportation sector. CAV technology forecasts vehicle and powertrain power needs under various terrain, ambient, and traffic conditions. Integration of the CAV technology in Hybrid Electric Vehicles (HEVs) provides the opportunity for optimal vehicle operation. Indeed, Hybrid Electric Vehicle powertrains present high degrees of flexibility and possibility for choosing optimum powertrain modes based on the predicted traction power needs. In modeling complex CAV powertrain dynamics, the modeler needs to consider short-time scale powertrain dynamics, such as engine transients, and hysteresis of mode-switching for a multi-mode HEV. Therefore, the powertrain dynamics essential for developing powertrain controllers for a class of connected HEVs is presented. To this end, control-oriented powertrain dynamic models for a test vehicle consisting of full electric, hybrid, and conventional engine operating modes are developed. The resulting powertrain model can forecast vehicle traction torque and energy consumption for the specified prediction horizon of the test vehicle. The model considers different operating modes and associated energy penalty terms for mode switching. Thus, the vehicle controller can determine the optimum powertrain mode, torque, and speed for forecasted vehicle operation via utilizing connectivity data. The powertrain model is validated against the experimental data and shows prediction error of less than 5% for predicting vehicle energy consumption. The model is used to create energy penalty maps that can be used for CAV control, for example fuel penalty map for engine torque changes (10–40 Nm) at each engine speed. The results of model-based optimization show optimum switching delays ranging from 0.4 to 1.4 s to avoid hysteresis in mode switching.

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 424
Samuel Kärnell ◽  
Liselott Ericson

There is growing interest in using electric motors as prime movers in mobile hydraulic systems. This increases the interest in so-called pump-controlled systems, where each actuator has its own drive unit. Such architectures are primarily appealing in applications where energy efficiency is important and electric recuperation is relevant. An issue with pump-controlled systems is, however, mode-switch oscillations which can appear when the pressure levels in the system are close to the switching condition. In this paper, the mode-switching behavior of different generalized closed and open circuit configurations is investigated. The results show that the choice of where to sense the pressures has a huge impact on the behavior. They also show that, if the pressure sensing components are properly placed, closed and open circuits can perform very similarly, but that mode-switch oscillations still can occur in all circuits. Active hysteresis control is suggested as a solution and its effectiveness is analyzed. The outcome from the analysis shows that active hysteresis control can reduce the risk for mode-switch oscillations significantly.

Nanoscale ◽  
2022 ◽  
Feifei Qin ◽  
Gangyi Zhu ◽  
Junbo Yang ◽  
Lai Wei ◽  
Qiannan Cui ◽  

Effective lasing mode control and unidirectional coupling of semiconductor microlasers are vital to boost their applications in optical interconnects, on-chip communication and bio-sensors. In this paper, symmetric and asymmetric GaN...

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 145
Hongdi Liu ◽  
Hongtao Zhang ◽  
Yuan He ◽  
Yong Sun

Modern adaptive radars can switch work modes to perform various missions and simultaneously use pulse parameter agility in each mode to improve survivability, which leads to a multiplicative increase in the decision-making complexity and declining performance of the existing jamming methods. In this paper, a two-level jamming decision-making framework is developed, based on which a dual Q-learning (DQL) model is proposed to optimize the jamming strategy and a dynamic method for jamming effectiveness evaluation is designed to update the model. Specifically, the jamming procedure is modeled as a finite Markov decision process. On this basis, the high-dimensional jamming action space is disassembled into two low-dimensional subspaces containing jamming mode and pulse parameters respectively, then two specialized Q-learning models with interaction are built to obtain the optimal solution. Moreover, the jamming effectiveness is evaluated through indicator vector distance measuring to acquire the feedback for the DQL model, where indicators are dynamically weighted to adapt to the environment. The experiments demonstrate the advantage of the proposed method in learning radar joint strategy of mode switching and parameter agility, shown as improving the average jamming-to-signal radio (JSR) by 4.05% while reducing the convergence time by 34.94% compared with the normal Q-learning method.

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