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Conceptual Design of the Low-Cost Environmental Temperature Test Chamber System
81-94Views:120Unmanned robots being remotely controlled or autonomous are spread worldwide and used in different purposes. Inhabited robots are brought very close to users and accessibility to these tools is very high, moreover, at very low costs. Regardless to emphasize the increasing popularity of these robots. However, any robot system being electrically driven and controlled has bottleneck in the amount of the electrical energy stored aboard in the battery packs. In other words, due to limited amount of the electrical energy available special issues related to use energy best way with maximum effectiveness are needed and considered. Additionally, the battery management system is needed to control the processes of the discharge and the charge ensuring technical data and parameters set by the manufacturer. This paper addresses robot applications in regions out of the calculated when special environmental testing is needed to confirm battery pack technical data. Among those of the environmental tests required the temperature test is in the focus of attention. The main idea and purpose of this paper is to set up new concept of the low-cost environmental temperature test chamber, to define its technical parameters and other properties needed for its preliminary design and prototype manufacturing.
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Battery Measurement Methods and Artificial Intelligence Applied in Energy Management Systems
428-436Views:154Diagnostics of batteries using advanced methods have gained remarkable roles in the past few years. This study focuses on the type of measurements, tests and methods to reveal and classify them. During manufacturing and operation several faults could emerge in batteries including non-optimal operation conditions, operators without experience, and finally, random changes in batteries under physical and nonphysical conditions. Improper handling of batteries and battery cells man cause operation failures or, in the worst case, accidents. To reveal these problems several methods are applied in industry and in scientific laboratories. For a comprehensive analysis of battery management, artificial intelligence and Industry 4.0 methods can be used very effectively. Big Data analysis in its standard form is not a new achievement, but other mathematical tools could be applied to control monitoring such as Fuzzy Logic or Support Vector Machine (SVM). They are efficient tools to analyse the deviation of batteries condition because it can detect sudden changes, parameter deviations and anomalies, and the user’s behaviour and habits. This article gives a description about the most important battery testing methods and the connection between Big Data and Operation Management with Artificial Intelligent (AI) methods.
