# Analysis of Instantaneous Energy Consumption and Recuperation Based on Measurements from SORT Runs
## 1 Introduction
Such a system helps to balance energy consumption and recovery, and SORTs can be used to evaluate these optimization solutions [16]. When planning routes, it is necessary to take into account factors such as road gradient, number of stops and passenger flows. The selection criteria for electric buses are closely related to their energy consumption and recuperation efficiency. A study conducted in Budapest using the TOPSIS method identified the main factors determining the choice of vehicle: maximum engine power, average specific fuel consumption, battery capacity, number of passengers, vehicle weight and road gradient. These things are very important for looking at how much energy buses use during SORTsbecause they allow one to see how efficient they are in different situations [17]. Using these indicators will help people to find the best approach for recovery and lower their energy use. Another important area is the application of digital twin technologies to the charging and control processes of electric buses [18]. Studies have shown that digital twin-based systems can coordinate bus charging, route allocation, battery storage, and solar power generation. This approach has led to reductions in emissions and electricity costs; for example, in electric bus depots emissions have been reduced by 98%, and in autonomous depots electricity costs have been reduced by between $3612 and $4010. By optimising recovery procedures and energy usage, SORT testing can aid in evaluating the practical effectiveness of these systems [19]. Practical considerations for choosing electric buses, including power consumption, charging duration, and failure frequency, were brought to light in research conducted by the Chinese Nanjing Bus Company. The effectiveness of the recovery process and the overall efficiency of the operation are impacted by these elements. When seeking to optimise fleet management, these criteria can be tested using SORT under real-world operating settings [20]. Furthermore, electric bus efficiency depends on performance and safety criteria. Research shows that, in order to increase the efficiency of energy regeneration, testing and evaluation of battery safety must be improved [21]. Degradation of batteries during heavy use might raise operational expenses and decrease recuperation efficiency, according to entropy weighting evaluation models [22]. In addition, the tests provide the data necessary for optimising drive systems, which are particularly important in assessing electric vehicles, where energy efficiency depends on the management of energy in the batteries [12; 23; 24]. Ref. [25] presents the results of the SORT-2 test conducted for an electric bus (the test is also known as E-SORT) by the UITP guidelines introduced in 2017, which allows for the estimation of the costs of electric energy consumption by the vehicle throughout its life cycle. Other examples of using SORT-2 tests can be found in [12; 26; 27; 28], which compared three types of drives: gas (CNG), diesel and electric. Operating conditions significantly impact the SORT results and are a key factor in assessing the efficiency of electric buses. Analysis of these conditions allows a better understanding of the factors influencing the test results and their representativeness for everyday vehicle operation. Factors influencing SORT results include vehicle weight and passenger load, where a heavier vehicle requires more energy, especially during acceleration and on steep routes. Another factor is the route topography--traffic on routes with different inclinations can lead to significant fluctuations in energy consumption and weather conditions, where, for example, extreme temperatures affect the operation of batteries and the energy consumption for heating or cooling [29]. Analysis of SORT results considering environmental variables allows for developing more precise energy consumption forecasts [30; 31].