scholarly journals Personalization of Electric Vehicle Accelerating Behavior Based on Motor Torque Adjustment to Improve Individual Driving Satisfaction

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3951
Author(s):  
Haksu Kim
Keyword(s):  
Electric Vehicles ◽  
High Performance ◽  
Internal Combustion Engines ◽  
Accelerator Pedal ◽  
Quantitative Characterization ◽  
Driving Style ◽  
Motor Torque ◽  
Propulsion Performance ◽  
Emission Regulations ◽  
The Individual

As worldwide vehicle CO2 emission regulations have been becoming more stringent, electric vehicles are regarded as one of the main development trends for the future automotive industry. Compared to conventional internal combustion engines, electric vehicles can generate a wider variety of longitudinal behaviors based on their high-performance motors and regenerative braking systems. The longitudinal behavior of a vehicle affects the driver’s driving satisfaction. Notably, each driver has their own driving style and as such demands a different performance for the vehicle. Therefore, personalization studies have been conducted in attempts to reduce the individual driving heterogeneity and thus improve driving satisfaction. In this respect, this paper first investigates a quantitative characterization of individual driving styles and then proposes a personalization algorithm of accelerating behavior of electric vehicles. The quantitative characterization determines the statistical expected value of the personal accelerating features. The accelerating features include physical values that can express acceleration behaviors and display different tendencies depending on the driving style. The quantified features are applied to calculate the correction factors for the target torque of the traction motor controller of electric vehicles. This driver-specific correction provides satisfactory propulsion performance for each driver. The proposed algorithm was validated through simulations. The results show that the proposed motor torque adjustment can reproduce different acceleration behaviors for an identical accelerator pedal input.

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

Improving Efficiency in Robot Assisted Belt Grinding of High Performance Materials

2014 ◽  
Vol 907 ◽  
pp. 139-149 ◽  
Author(s):  
Eckart Uhlmann ◽  
Florian Heitmüller
Keyword(s):  
Gas Turbines ◽  
High Performance ◽  
Scale Effects ◽  
Turbine Blades ◽  
Repair Process ◽  
Industrial Robots ◽  
Robot Assisted ◽  
Belt Grinding ◽  
Economy Of Scale ◽  
The Individual

In gas turbines and turbo jet engines, high performance materials such as nickel-based alloys are widely used for blades and vanes. In the case of repair, finishing of complex turbine blades made of high performance materials is carried out predominantly manually. The repair process is therefore quite time consuming. And the costs of presently available repair strategies, especially for integrated parts, are high, due to the individual process planning and great amount of manually performed work steps. Moreover, there are severe risks of partial damage during manually conducted repair. All that leads to the fact that economy of scale effects remain widely unused for repair tasks, although the piece number of components to be repaired is increasing significantly. In the future, a persistent automation of the repair process chain should be achieved by developing adaptive robot assisted finishing strategies. The goal of this research is to use the automation potential for repair tasks by developing a technology that enables industrial robots to re-contour turbine blades via force controlled belt grinding.

Adaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software

2021 ◽  
Vol 47 (2) ◽  
pp. 1-28
Author(s):  
Goran Flegar ◽  
Hartwig Anzt ◽  
Terry Cojean ◽  
Enrique S. Quintana-Ortí
Keyword(s):  
Linear Algebra ◽  
Graphics Processing Units ◽  
High Performance ◽  
Numerical Algorithms ◽  
Mixed Precision ◽  
Before And After ◽  
Memory Accesses ◽  
Specialized Hardware ◽  
The Individual ◽  
Graphics Processing

The use of mixed precision in numerical algorithms is a promising strategy for accelerating scientific applications. In particular, the adoption of specialized hardware and data formats for low-precision arithmetic in high-end GPUs (graphics processing units) has motivated numerous efforts aiming at carefully reducing the working precision in order to speed up the computations. For algorithms whose performance is bound by the memory bandwidth, the idea of compressing its data before (and after) memory accesses has received considerable attention. One idea is to store an approximate operator–like a preconditioner–in lower than working precision hopefully without impacting the algorithm output. We realize the first high-performance implementation of an adaptive precision block-Jacobi preconditioner which selects the precision format used to store the preconditioner data on-the-fly, taking into account the numerical properties of the individual preconditioner blocks. We implement the adaptive block-Jacobi preconditioner as production-ready functionality in the Ginkgo linear algebra library, considering not only the precision formats that are part of the IEEE standard, but also customized formats which optimize the length of the exponent and significand to the characteristics of the preconditioner blocks. Experiments run on a state-of-the-art GPU accelerator show that our implementation offers attractive runtime savings.

Compositional Analysis of Organosolv Poplar Lignin by Using High-Performance Liquid Chromatography/High-resolution Multi-stage Tandem Mass Spectrometry

2021 ◽  
Author(s):  
Jifa Zhang ◽  
Yuan Jiang ◽  
Leah F Easterling ◽  
Anton Anster ◽  
Wanru Li ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Performance ◽  
Compositional Analysis ◽  
Complex Mixtures ◽  
Tandem Mass ◽  
Multi Stage ◽  
The Individual ◽  
Environmentally Friendly Process

Organosolv treatment is an efficient and environmentally friendly process to degrade lignin into small compounds. The capability of characterizing the individual compounds in the complex mixtures formed upon organosolv treatment...

scholarly journals Crosses with spelt improve tolerance of South Asian spring wheat to spot blotch, terminal heat stress, and their combination

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ajeet Kumar Pandey ◽  
Vinod Kumar Mishra ◽  
Ramesh Chand ◽  
Sudhir Navathe ◽  
Neeraj Budhlakoti ◽  
...  
Keyword(s):  
Grain Yield ◽  
Spring Wheat ◽  
High Performance ◽  
Recombinant Inbred Lines ◽  
Spot Blotch ◽  
Spikelet Sterility ◽  
Strong Negative Correlation ◽  
Terminal Heat Stress ◽  
H 26 ◽  
The Individual

AbstractSpot blotch and terminal heat are two of the most important stresses for wheat in South Asia. A study was initiated to explore the use of spelt (Triticum spelta) to improve tolerance to these stresses in spring wheat (T. aestivum). We assessed 185 recombinant inbred lines (RILs) from the cross T. spelta (H + 26) × T. aestivum (cv. HUW234), under the individual stresses and their combination. H + 26 showed better tolerance to the single stresses and also their combination; grain yield in RILs was reduced by 21.9%, 27.7% and 39.0% under spot blotch, terminal heat and their combined effect, respectively. However, phenological and plant architectural traits were not affected by spot blotch itself. Multivariate analysis demonstrated a strong negative correlation between spikelet sterility and grain yield under spot blotch, terminal heat and their combination. However, four recombinant lines demonstrated high performance under both stresses and also under their combined stress. The four lines were significantly superior in grain yield and showed significantly lower AUDPC than the better parent. This study demonstrates the potential of spelt wheat in enhancing tolerance to spot blotch and terminal heat stresses. It also provides comprehensive evidence about the expression of yield and phenological traits under these stresses.

scholarly journals Input Parallel Output Series Structure of Planar Medium Frequency Transformers for 200 kW Power Converter: Model and Parameters Evaluation

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1450
Author(s):  
Alessandro La Ganga ◽  
Roberto Re ◽  
Paolo Guglielmi
Keyword(s):  
Electric Vehicles ◽  
High Performance ◽  
Power Converter ◽  
Electrical Model ◽  
Solid State Transformer ◽  
Medium Frequency ◽  
Analytical Treatment ◽  
Transformer Model ◽  
Planar Medium ◽  
Parallel Output

Nowadays, the demand for high power converters for DC applications, such as renewable sources or ultra-fast chargers for electric vehicles, is constantly growing. Galvanic isolation is mandatory in most of these applications. In this context, the Solid State Transformer (SST) converter plays a fundamental role. The adoption of the Medium Frequency Transformers (MFT) guarantees galvanic isolation in addition to high performance in reduced size. In the present paper, a multi MFT structure is proposed as a solution to improve the power density and the modularity of the system. Starting from 20kW planar transformer model, experimentally validated, a multi-transformer structure is analyzed. After an analytical treatment of the Input Parallel Output Series (IPOS) structure, an equivalent electrical model of a 200kW IPOS (made by 10 MFTs) is introduced. The model is validated by experimental measurements and tests.

scholarly journals To Represent Electric Vehicles in Electricity Systems Modelling—Aggregated Vehicle Representation vs. Individual Driving Profiles

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 539
Author(s):  
Maria Taljegard ◽  
Lisa Göransson ◽  
Mikael Odenberger ◽  
Filip Johnsson
Keyword(s):  
Electric Vehicles ◽  
Investment Model ◽  
Research Issues ◽  
Charging Infrastructure ◽  
Vehicle To Grid ◽  
Long Term Storage ◽  
Electricity System ◽  
Home Location ◽  
The Individual ◽  
Storage Technologies

This study describes, applies, and compares three different approaches to integrate electric vehicles (EVs) in a cost-minimising electricity system investment model and a dispatch model. The approaches include both an aggregated vehicle representation and individual driving profiles of passenger EVs. The driving patterns of 426 randomly selected vehicles in Sweden were recorded between 30 and 73 days each and used as input to the electricity system model for the individual driving profiles. The main conclusion is that an aggregated vehicle representation gives similar results as when including individual driving profiles for most scenarios modelled. However, this study also concludes that it is important to represent the heterogeneity of individual driving profiles in electricity system optimisation models when: (i) charging infrastructure is limited to only the home location in regions with a high share of solar and wind power in the electricity system, and (ii) when addressing special research issues such as impact of vehicle-to-grid (V2G) on battery health status. An aggregated vehicle representation will, if the charging infrastructure is limited to only home location, over-estimate the V2G potential resulting in a higher share (up to 10 percentage points) of variable renewable electricity generation and an under-estimation of investments in both short- and long-term storage technologies.

Dioxazine pigments

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Robert Christie ◽  
Adrian Abel
Keyword(s):  
High Performance ◽  
Industrial Applications ◽  
Textile Dye ◽  
Linear Arrangement ◽  
Natural Colorant ◽  
X Ray ◽  
Organic Pigments ◽  
Tyrian Purple ◽  
Violet Color ◽  
The Individual

Abstract This chapter provides an overview of the structural and synthetic chemistry, and the industrial applications, of dioxazine pigments, a small group of high performance organic pigments. The color violet (or purple) has frequently assumed a prominent position in history, on account of its rarity and cost. The natural colorant Tyrian purple and the first synthetic textile dye, Mauveine, are prime examples of this unique historical feature. CI Pigment Violet 23, also referred to as Dioxazine Violet or Carbazole Violet, is one of the most universally used organic pigments, by far the most important industrial pigment in the violet shade area. Dioxazine Violet is also unique as the dominant industrial violet pigment providing a brilliant, intense violet color and an excellent all-round set of fastness properties. The pigment has a polycyclic molecular structure, originally described wrongly as a linear arrangement, and later shown to adopt an S-shaped arrangement on the basis of X-ray structural analysis. Two other dioxazine pigments are of rather lesser importance. The synthesis and manufacturing route to CI Pigment Violet 23 is described in the review. Finally, a survey of the principal current applications of the individual dioxazine pigments is presented.

scholarly journals Modelling Stochastic Electricity Demand of Electric Vehicles Based on Traffic Surveys—The Case of Austria

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1577
Author(s):  
Albert Hiesl ◽  
Jasmine Ramsebner ◽  
Reinhard Haas
Keyword(s):  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Length Distribution ◽  
Electricity Demand ◽  
Transport Sector ◽  
Trip Purpose ◽  
Entire Country ◽  
Electricity Load ◽  
The Individual ◽  
Model Based Analysis

Battery-powered electric mobility is currently the most promising technology for the decarbonisation of the transport sector, alongside hydrogen-powered vehicles, provided that the electricity used comes 100% from renewable energy sources. To estimate its electricity demand both nationwide and in individual smaller communities, a calculation based assessment on driving profiles that are as realistic as possible is required. The developed model based analysis presented in this paper for the creation of driving and thus electricity load profiles makes it possible to build different compositions of driving profiles. The focus of this paper lies in the analysis of motorised private transport, which makes it possible to assess future charging and load control potentials in a subsequent analysis. We outline the differences in demand and driving profiles for weekdays as well as for Saturdays, Sundays and holidays in general. Furthermore, the modelling considers the length distribution of the individual trips per trip purpose and different start times. The developed method allows to create individual driving and electric vehicle (EV) demand profiles as well as averaged driving profiles, which can then be scaled up and analysed for an entire country.

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