Dependency of Machine Efficiency on the Thermal Behavior of Induction Machines

Machines ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 9
Author(s):  
Svenja Kalt ◽  
Karl Ludwig Stolle ◽  
Philipp Neuhaus ◽  
Thomas Herrmann ◽  
Alexander Koch ◽  
...  
Keyword(s):  
Thermal Behavior ◽  
Electric Vehicles ◽  
Thermal Load ◽  
Load Capacity ◽  
Maximum Load ◽  
Induction Machines ◽  
Electric Machines ◽  
Model Parameters ◽  
Dynamic Operating ◽  
The Impact

The consideration of the thermal behavior of electric machines is becoming increasingly important in the machine design for electric vehicles due to the adaptation to more dynamic operating points compared to stationary applications. Whereas, the dependency of machine efficiency on thermal behavior is caused due to the impact of temperature on the resulting loss types. This leads to a shift of efficiency areas in the efficiency diagram of electric machines and has a significant impact on the maximum load capability and an impact on the cycle efficiency during operation, resulting in a reduction in the overall range of the electric vehicle. Therefore, this article aims at analyzing the thermal load limits of induction machines in regard to actual operation using measured driving data of battery electric vehicles. For this, a thermal model is implemented using MATLAB® and investigations to the sensitivity of model parameters as well as analysis of the continuous load capacity, thermal load and efficiency in driving cycles under changing boundary conditions are conducted.

scholarly journals Preliminary Design Framework for the Power Gearbox in a Contra-Rotating Open Rotor

2020 ◽  
Author(s):  
Diana G. San Benito Pastor ◽  
Devaiah Nalianda ◽  
Vishal Sethi ◽  
Ron Midgley ◽  
Andrew Rolt ◽  
...  
Keyword(s):  
System Design ◽  
Load Capacity ◽  
Engine Performance ◽  
Maximum Load ◽  
Transmission System ◽  
Published Data ◽  
Planetary Gearbox ◽  
Open Rotor ◽  
Parametric Analyses ◽  
The Impact

Abstract This study introduces an innovative approach to sizing a differential planetary gearbox for a counter-rotating open rotor application. An updated methodology is proposed for the design of maximum load capacity gears based on the power transmitted, durability and space-envelope requirements of the application. The reported methodology has been validated by comparing the results to published data, demonstrating a maximum difference of 0.6% in geometry. Parametric analyses have also been performed to assess the impact of the design assumptions on gearbox dimensional trends. The proposed methodology enables the assessment of the impact of the preliminary transmission system design on engine performance and general arrangement. The characteristics of the gearset lead to an unequal torque split between output shafts (i.e. the propeller shafts). Given the design assumptions made, the study indicates that valid torque ratios would lie between 1.1 and 1.33. The impact of the torque ratio on the size of the gearbox has been analysed for equal rotational speeds and for different speeds between the output shafts. The study established that the transmission system design needs to be considered prior to selection of the torque ratio at engine design level.

scholarly journals Concept Design and Load Capacity Analysis of a Novel Serial-Parallel Robot for the Automatic Charging of Electric Vehicles

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 956
Author(s):  
Han Yuan ◽  
Qiong Wu ◽  
Lili Zhou
Keyword(s):  
Electric Vehicles ◽  
Load Capacity ◽  
Structural Parameters ◽  
Maximum Load ◽  
Parallel Robot ◽  
Driving Ability ◽  
Concept Design ◽  
Electric Vehicle Charging ◽  
Pulling Forces ◽  
High Load Capacity

The automatic charging of electric vehicles is an important but challenging problem. Recently, various charging robots are proposed for electric vehicles. Most previous researches do not pay enough attention to the robots’ load capacities. Actually, providing the charging connector with adequate pushing and/or pulling forces is vital to guarantee a reliable electrical connection, which is a key issue for charging robot design. In this paper, we present a novel serial-parallel robot for the automatic charging of electric vehicles. This robot is based on the 3 universal-prismatic-universal (3UPU) parallel mechanism and featured by high-load capacity. We firstly address the kinematic and static models of the proposed robot, then analyze its load capacity. It is shown that the robot’s maximum load capacity depends not only on the driving ability of the prismatic joints, but also on the robot’s structural parameters and the robot’s configuration. Finally, optimizations are made and results show that the robot’s load capacity along the desired trajectory has more than doubled. Results of this paper could be useful for the development of automatic electric-vehicle-charging devices.

Challenges in Validating a Thermo-Hydrodynamic Gas Foil Bearing Model

2020 ◽  
Author(s):  
Hanns Michel ◽  
Robert Liebich
Keyword(s):  
Thermal Model ◽  
High Speed ◽  
Load Capacity ◽  
Maximum Load ◽  
Fine Tuning ◽  
Flow Paths ◽  
Operational Conditions ◽  
Foil Bearings ◽  
Wide Range ◽  
The Impact

Abstract Gas foil bearings (GFBs) are suitable for high speed and temperature applications where conventional lubricated bearing solution are not feasible. This requires the pre-diction of bearing temperatures and thus a thermal model considering the heat genera-tion and heat flow paths in the bearing. The effects of two different bump foil stiffness (Iordanoff and Le Lez [1,2]) and heat transfer models (a simplified and a detailed one) are presented in respect to measured temperatures from literature [3,4]. The compari-son is drawn over a wide range of operational conditions as well as measuring posi-tions, which in such detail has not been shown before. While good agreement is found for some of the conditions and positions, only reasonable agreement is found for others. The deviations and difficulties in validating a thermal model against experiments are highlighted in a discussion about various temperature influencing parameters, especial-ly concerning the change of clearance during operation. In conclusion it is found, that the models are able to predict temperatures reasonably well, but require delicate fine-tuning to achieve these results. Finally, the impact of the temperature on the maximum load capacity at a range of speeds is shown in a comparison between an isothermal calculation and one with temperature consideration.

Thermal Storage Systems for District Heating Networks

2010 ◽  
Author(s):  
Vittorio Verda ◽  
Francesco Colella
Keyword(s):  
Electricity Market ◽  
Thermal Load ◽  
Storage Systems ◽  
Fluid Dynamic ◽  
District Heating ◽  
Heating System ◽  
Maximum Load ◽  
Operating Conditions ◽  
District Heating System ◽  
The Impact

District Heating is an efficient way to provide heat to residential, tertiary and industrial users. Heat is often produced by CPH plants, usually designed to provide the base thermal load (40–50% if the maximum load) while the rest is provided by boilers. This choice is made on the basis of economic criteria, in fact the investment cost of a CHP plant is much higher than the cost of boiler, thus its use is convenient when it operates for a large number of hours. The use of storage tanks would permit to increase the annual operating hours of CHP: heat can be produced when the request is low (for instance during the night), stored and then used when the request is high. The use of boilers results partially reduced, thus the thermal load diagram is flattered. Depending on the type of CHP plant this may also affect the electricity generation. All these considerations are crucial in the free electricity market. In this paper, the use of storage systems connected to the district heating systems, is examined. A thermo fluid dynamic model of the tanks is considered in order to calculate the amount of energy actually provided, taking the real operating conditions into account. These considerations are applied to the Turin district heating system, in order to determine the impact of storage systems on the primary energy consumption required to supply heat to the users over the entire heating season.

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

scholarly journals Advances of 2nd Life Applications for Lithium Ion Batteries from Electric Vehicles Based on Energy Demand

2021 ◽  
Vol 13 (10) ◽  
pp. 5726
Author(s):  
Aleksandra Wewer ◽  
Pinar Bilge ◽  
Franz Dietrich
Keyword(s):  
Life Cycle ◽  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Energy Demand ◽  
Lithium Ion ◽  
Life Cycles ◽  
Future Research ◽  
Research Areas ◽  
Study Results ◽  
The Impact

Electromobility is a new approach to the reduction of CO2 emissions and the deceleration of global warming. Its environmental impacts are often compared to traditional mobility solutions based on gasoline or diesel engines. The comparison pertains mostly to the single life cycle of a battery. The impact of multiple life cycles remains an important, and yet unanswered, question. The aim of this paper is to demonstrate advances of 2nd life applications for lithium ion batteries from electric vehicles based on their energy demand. Therefore, it highlights the limitations of a conventional life cycle analysis (LCA) and presents a supplementary method of analysis by providing the design and results of a meta study on the environmental impact of lithium ion batteries. The study focuses on energy demand, and investigates its total impact for different cases considering 2nd life applications such as (C1) material recycling, (C2) repurposing and (C3) reuse. Required reprocessing methods such as remanufacturing of batteries lie at the basis of these 2nd life applications. Batteries are used in their 2nd lives for stationary energy storage (C2, repurpose) and electric vehicles (C3, reuse). The study results confirm that both of these 2nd life applications require less energy than the recycling of batteries at the end of their first life and the production of new batteries. The paper concludes by identifying future research areas in order to generate precise forecasts for 2nd life applications and their industrial dissemination.

scholarly journals Evolution of disease transmission during the COVID-19 pandemic: patterns and determinants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Clustering Algorithm ◽  
Health Interventions ◽  
Transmission Model ◽  
Model Parameters ◽  
Public Health Interventions ◽  
Forecasting Accuracy ◽  
Time Lagged ◽  
The Impact

AbstractEpidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ($$R_t$$ R t ). The relationship between public health interventions and $$R_t$$ R t was explored, firstly using a hierarchical clustering algorithm on initial $$R_t$$ R t patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, $$R_t$$ R t , and daily incidence counts in subsequent months. The impact of updating $$R_t$$ R t every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future $$R_t$$ R t (75 days lag), while a lower $$R_t$$ R t was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated $$R_t$$ R t produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when $$R_t$$ R t was kept constant. Monitoring the evolution of $$R_t$$ R t during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated $$R_t$$ R t values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of $$R_t$$ R t over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.

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