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This paper presents an energy efficient power coupling steering system for dual motors drive high speed tracked vehicle. The system consists of a new type of center steering motor, two electromagnetic (EM) clutches, two planetary gear couplers, and two propulsion motors. The motor torque and power required by dynamic steering with different steering radiuses for dual motors drive high speed tracked vehicle were investigated. A motor-speed-based control strategy of dynamic steering is designed to achieve vehicle lateral stability enhancement. The model of the proposed control strategy in RecuDyn and Matlab/Simulink is given. The simulation results of dynamic steering with 0.5B and 2B radius show that understeer in small radius steering can be significantly improved.

In this article, a systematic literature review of 419 articles on energy demand modeling, published between 2015 and 2020, is presented. This provides researchers with an exhaustive overview of the examined literature and classification of techniques for energy demand modeling. Unlike in existing literature reviews, in this comprehensive study all of the following aspects of energy demand models are analyzed: techniques, prediction accuracy, inputs, energy carrier, sector, temporal horizon, and spatial granularity. Readers benefit from easy access to a broad literature base and find decision support when choosing suitable data-model combinations for their projects. Results have been compiled in comprehensive figures and tables, providing a structured summary of the literature, and containing direct references to the analyzed articles. Drawbacks of techniques are discussed as well as countermeasures. The results show that among the articles, machine learning (ML) techniques are used the most, are mainly applied to short-term electricity forecasting on a regional level and rely on historic load as their main data source. Engineering-based models are less dependent on historic load data and cover appliance consumption on long temporal horizons. Metaheuristic and uncertainty techniques are often used in hybrid models. Statistical techniques are frequently used for energy demand modeling as well and often serve as benchmarks for other techniques. Among the articles, the accuracy measured by mean average percentage error (MAPE) proved to be on similar levels for all techniques. This review eases the reader into the subject matter by presenting the emphases that have been made in the current literature, suggesting future research directions, and providing the basis for quantitative testing of hypotheses regarding applicability and dominance of specific methods for sub-categories of demand modeling.

AbstractChina is globally the largest and a rapidly growing market for electric vehicles. The aim of the paper is to determine challenges related to criticality and environmental impacts of battery electric vehicles and internal combustion engine vehicles, focusing not only on a global but also the Chinese perspective, applying the ESSENZ method, which covers a unique approach to determine criticality aspects as well as integrating life cycle assessment results. Real industry data for vehicles and batteries produced in China was collected. Further, for the criticality assessment, Chinese import patterns are analyzed. The results show that the battery electric vehicle has similar and partly increased environmental impacts compared with the internal combustion engine vehicle. For both, the vehicle cycle contributes to a large proportion in all the environmental impact categories except for global warming. Further, battery electric vehicles show a higher criticality than internal combustion engine vehicles, with tantalum, lithium, and cobalt playing essential roles. In addition, the Chinese-specific results show a lower criticality compared to the global assessment for the considered categories trade barriers and political stability, while again tantalum crude oil and cobalt have high potential supply disruptions. Concluding, battery electric vehicles still face challenges regarding their environmental as well as criticality performance from the whole supply chain both in China and worldwide. One reason is the replacement of the lithium-ion power battery. By enhancing its quality and establishing battery recycling, the impacts of battery electric vehicle would decrease.

In the next decade, further digitalisation of the entire wind energy project lifecycle is expected to be a major driver for reducing project costs and risks. In this paper, a literature review on the challenges related to implementation of digitalisation in the wind energy industry is first carried out, showing that there is a strong need for new solutions that enable co-innovation within and between organisations. Therefore, a new collaboration method based on a digital ecosystem is developed and demonstrated. The method is centred around specific “challenges”, which are defined by “challenge providers” within a topical “space” and made available to participants via a digital platform. The data required in order to solve a particular “challenge” are provided by the “challenge providers” under the confidentiality conditions they specify. The method is demonstrated via a case study, the EDP Wind Turbine Fault Detection Challenge. Six submitted solutions using diverse approaches are evaluated. Two of the solutions perform significantly better than EDP’s existing solution in terms of Total Prediction Costs (saving up to €120,000). The digital ecosystem is found to be a promising solution for enabling co-innovation in wind energy in general, providing a number of tangible benefits for both challenge and solution providers.

This study is about a method for evaluating specific product complexity. In this context, an efficient and scalable method for the development of a specific complexity assessment of highly complex products is presented. Furthermore, existing evaluation methods are analysed according to effort and benefit, thus showing the research gap and the need for the method to be developed. The procedure for the development of an indicator for the specific evaluation of product complexity is presented in five steps and an exemplary complexity indicator for lithium ion battery cells is developed. This index is then applied, and the complexity of commercial battery cells from the application is evaluated. Based on these evaluations, final potentials of the method are shown and a recommendation for a reduction in product complexity is provided. The developed method for complexity assessment is scalable in its effort and offers implementation into existing complexity management. The method allows quick adaptation or extension and, thus, well-founded decision making. By standardizing the evaluation and taking objectively measurable complexity characteristic values as a basis, a holistic and objective evaluation tool is shown, which can thus become a decisive success factor for manufacturers of complex products.

In order to characterize high temperature polymer electrolyte fuel cells (HT-PEFCs) in operando, neutron radiography imaging, in combination with the deuterium contrast method, was used to analyze the hydrogen distribution and proton exchange processes in operando. These measurements were then combined with the electrochemical impedance spectroscopy measurements. The cell was operated under different current densities and stoichiometries. Neutron images of the active area of the cell were captured in order to study the changeover times when the fuel supply was switched between hydrogen and deuterium, as well as to analyze the cell during steady state conditions. This work demonstrates that the changeover from proton to deuteron (and vice versa) leads to local varying media distributions in the electrolyte, independent of the overall exchange dynamics. A faster proton-to-deuteron exchange was re-discovered when switching the gas supply from H2 to D2 than that from D2 to H2. Furthermore, the D2 uptake and discharge were faster at a higher current density. Specifically, the changeover from H to D takes 5–6 min at 200 mA cm−2, 2–3 min at 400 mA cm−2 and 1–2 min at 600 mA cm−2. An effect on the transmittance changes is apparent when the stoichiometry changes.

AbstractThe basic concepts and advantages of more/all electric aircraft (M/AEA) are briefly addressed. The combined starter/generator (CS/G) system is introduced as a key technology to enable M/AEA. Some important performance requirements for CS/G system are obtained. Based on these requirements, a high speed switched reluctance machine (SRM) is designed to operate as a starter/generator. The entire design process is mainly divided into two stages: electromagnetic design and thermal design. In electromagnetic design stage, the electromagnetic structure and dimensions of the machine and the number of phase winding turns per pole are obtained; the topology and main technical details of the converter are briefly introduced as well. In thermal design stage, a liquid-cooling system is designed based on the thermal analysis of the machine. In the end, the performances of the designed SRM are basically verified by simulation. To get high performances, the exciting angles are optimized in two different operating modes respectively, and the optimized performances in the motoring mode are given as well.