Modeling rebound effects and counteracting policies for German industries

Ahmann, Lara; Banning, Maximilian; Lutz, Christian

doi:10.1016/j.ecolecon.2022.107432

Cited by 4 publications

(1 citation statement)

References 44 publications

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“…A new energy vehicle is a vehicle that uses a new type of power system, such as an electric motor, battery, fuel cell, etc., instead of the traditional internal combustion engine as the driving power. 1,2 The development of new energy vehicles is of great significance for improving environmental quality, promoting energy transformation, and realizing the sustainable development of the automobile industry. By strengthening the research on new energy vehicles, the performance and range of vehicles can be further improved, the manufacturing cost can be reduced, the popularization and application of new energy vehicles can be promoted, and a greener and cleaner way of traveling can be created for human beings.…”

Section: Introductionmentioning

confidence: 99%

Fault data enhancement and real-time diagnosis using optimized ViT ++ algorithm for electric drive system

Zheng,

Fang,

Jin

et al. 2024

Advances in Mechanical Engineering

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With the rapid development of electric drive technology for new energy vehicles, fault data identification of key components of electric drives has become a crucial issue in improving the stability and safety of electric systems. However, traditional fault data recognition methods have many limitations in dealing with complex and variable operating fault situations. To address this problem, this paper proposes a deep learning model, Vision Transformer Plus (ViT++), based on the self-attention mechanism and combined with data enhancement strategies for fault identification of energy vehicle electric drive system. Accurately identifying fault types is achieved by transforming the electric drive system fault data into an image matrix and performing feature extraction and learning with the help of the ViT model. To validate the effectiveness of the proposed method, we conducted extensive cross-experiments using a large amount of actual electric drive key component fault data and applying a data enhancement strategy. The experimental results show that the fault data recognition method based on the ViT algorithm has higher accuracy and robustness than the traditional convolutional neural network (CNN)-based method. Therefore, the proposed method in this paper is conducive to improving the accuracy and efficiency of fault data identification for key components in electric vehicles, thus playing a critical role in analyzing electric drive system faults.

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Section: Introductionmentioning

confidence: 99%

Fault data enhancement and real-time diagnosis using optimized ViT ++ algorithm for electric drive system

Zheng,

Fang,

Jin

et al. 2024

Advances in Mechanical Engineering

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Effects of Energy Price Shocks on Germany’s Economy and Private Households

Lutz

Becker

2023

Studies in Energy, Resource and Environmental Economics

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The massive rise in energy prices in the wake of the Ukraine crisis and the Western sanctions against Russia is putting a great strain on the economy and consumers. Germany is particularly dependent on Russian energy imports. With the desire to reduce dependence on Russian imports, the pressure for climate neutrality is intensifying. The reports of the IPCC recently show again the high pressure to act. The EU is aiming for climate neutrality by 2050, and Germany would like to reach the target by 2045.This chapter aims to examine the macroeconomic effects of the drastic price increase for energy sources in Germany. For this purpose, a scenario in which energy prices on the world market experience a significant shock is compared with a reference scenario until 2030. The scenarios are implemented in the economy–energy–environment model PANTA RHEI. The scenario comparison shows the different effects of energy price increase on important macroeconomic variables such as price level for consumers, GDP, and employment. Distributional effects across income classes are considered with particular attention to low-income households, which spend higher shares of their income for energy and cannot afford to pay for energy efficiency improvement. A brief comparison with other modelling studies shows that climate mitigation has a positive effect on the economy as a whole and can be an important lever for containing the losses caused by the current high energy prices.

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The policy evaluation of China's carbon emissions trading scheme on firm employment: A channel from industrial automation

Wang

Song

2023

Energy Policy

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Modeling rebound effects and counteracting policies for German industries

Cited by 4 publications

References 44 publications

Fault data enhancement and real-time diagnosis using optimized ViT ++ algorithm for electric drive system

Fault data enhancement and real-time diagnosis using optimized ViT ++ algorithm for electric drive system

Effects of Energy Price Shocks on Germany’s Economy and Private Households

The policy evaluation of China's carbon emissions trading scheme on firm employment: A channel from industrial automation

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