Lithium-ion batteries are complex systems and making a simulation model of them is always challenging. A method for producing an accurate model with high capabilities for predicting the behavior of the battery in a time and cost efficient way is desired in this field of work. The aim of this thesis has been to develop a method to be close to the desired method as much as possible, especially in two important aspects, time and cost. The method which is the goal of this thesis should fulfill the below five requirements: 1. Able to produce a generic battery model for different types of lithium-ion batteries 2. No or low cost for the development of the model 3. A time span around one week for obtaining the model 4. Able to predict the most aspects of the battery’s behavior like the voltage, SOC, temperature and, preferably, simulate the degradation effects, safety and thermal aspects 5. Accuracy with less than 15% error The start point of this thesis was the study of current methods for cell modeling. Based on their approach, they are divided into three categories, abstract, black box and white box methods. Each of these methods has its own advantages and disadvantages, but none of them are able to fulfill the above requirements. This thesis presents a method, called “gray box”, which is, partially, a mix of the black and white boxes’ concepts. The gray box method uses values for model’s parameters from different sources. Firstly, some chemical/physical measurements like in the case of the white box method, secondly, some of the physical tests/experiments used in the case of the black box method and thirdly, information provided by cell datasheets, books, papers, journals and scientific databases. As practical part of this thesis, a prismatic cell, EIG C20 with 20Ah capacity was selected as the sample cell and its electrochemical model was produced with the proposed method. Some of the model’s parameters are measured and some others are estimated. Also, the abilities of AutoLion, a specialized software for lithium-ion battery modeling were used to accelerate the modeling process. Finally, the physical tests were used as part of the references for calculating the accuracy of the produced model. The results show that the gray box method can produce a model with nearly no cost, in less than one week and with error around 30% for the HPPC tests and, less than this, for the OCV and voltage tests. The proposed method could, largely, fulfill the five mentioned requirements. These results were achieved even without using any physical tests/experimental data for tuning the parameters, which is expected to reduce the error considerably. These are promising results for the idea of the gray box which is in its nascent stages and needs time to develop and be useful for commercial purposes.

The relevance of the topic is due to the fact that copper is used in all sectors of industry: engineering, electrical industry, household industry, construction, etc. It produces wires and cables, pipes, cooling systems and much more. Thus, the scope of copper is constantly expanding, so the need for it is growing from year to year. Copper mining from natural sources is expensive and not environmentally friendly. Therefore, it is much more efficient to produce copper by secondary processing. In modern conditions, it is important to be able to predict the resource base of the enterprise in the short and long term, because this helps to direct investments in the right direction and to avoid economic losses. The aim of the work is to build a predictive model of the copper scrap market using key parameters. Tasks of work: • to consider the theoretical aspects of the development of the Russian copper scrap market; • to evaluate key indicators of the copper scrap market and adjust the model characterizing the dynamics of the volume of copper scrap; • to develop a forecast model and produce a forecast; • to analyze the enterprises of the metallurgy market; • to identify the behavior strategies of agents in the copper scrap market and build a diagram of competitive behavior strategies; • to evaluate the effectiveness of the competitive behavior strategy chart; • to evaluate the economic efficiency of creating a new information system. / Актуальность темы обусловлена тем, что медь используется во всех секторах промышленности: для машиностроения, электротехнической промышленности, бытовой промышленности, в строительстве и т.д. Из нее изготавливаются провода и кабели, трубы, системы охлаждения и многое другое. Таким образом, сферы применения меди постоянно расширяются, поэтому потребности в ней растут из года в год. Добыча меди из природных источников процесс дорогостоящий и не экологичный. Поэтому гораздо эффективнее получать медь путем вторичной обработки. В современных условиях, важно уметь прогнозировать ресурсную базу предприятия в краткосрочной и долгосрочной перспективе, т.к. это помогает направить инвестиции в нужное русло и избежать экономических потерь. Целью работы является построение прогнозной модели рынка медного лома с использованием ключевых параметров. Задачи работы: • рассмотреть теоретические аспекты развития рынка медного лома РФ; • оценить ключевые показатели рынка медного лома и скорректировать модель, характеризующую динамику объема медного лома; • разработать прогнозную модель и произвести прогноз; • провести анализ предприятий рынка металлургии; • выявить стратегии поведения агентов на рынке медного лома и построить диаграмму конкурентной стратегии поведения; • оценить эффективность диаграммы конкурентной стратегии поведения; • оценить экономическую эффективность создания новой информационной системы.