# Concept for Generating Energy Demand in Electric Vehicles with a Model Based Approach
## 1 Introduction  
The entire transport system is in the midst of a transformation. In December 2020, the European Commission presented a new strategy (The European Green Deal) for sustainable and intelligent mobility. The goal is to reduce transport emissions by 90% by the year 2050 through smart and competitive technologies [1]. In order to accomplish this goal, automotive manufacturers must increasingly focus on powertrain technologies that are more environmentally friendly and cost-efficient. As a result, the topic of electric vehicles has become increasingly important in recent years [2]. The development of electric vehicles is nowadays strongly driven by customer demand with regard to environmental factors and economic aspects [3]. At the same time, one of the key issues in the development ofelectric vehicles is the energy storage system [4]. The comparatively high cost and limited lifetime of batteries limit the development of electric vehicles in certain areas [5]. In recent years, research has been conducted on a variety of types of batteries with the objective to improve their efficiency and performance [4]. In addition, supercapacitors have been used in the context of hybrid energy storage systems to take advantage of the new opportunities they offer [4]. To operate such a hybrid energy storage system, it needs an intelligent and optimized management system. The potential risk of a non-optimized management system is that it could significantly shorten the battery life due to unfavorable loads and inefficient use of the energy [6]. Furthermore, a non-optimized management system can shorten the lithium-ion battery's life due to over-voltage, over-temperature and rapid discharge and charge of the lithium-ion battery cell [7]. For the development and especially for the model-based validation of an energy management system, knowledge about the vehicle and the route resulting in the energy consumption of the vehicle is needed [8]. Many studies work with synthetic, standardized driving cycles (e.g., New European Driving Cycle (NEDC), Worldwide Harmonised Light-Duty Vehicles Test Procedure (WLTP)) and the energy consumption data collected there [9; 10; 11; 12; 13; 14]. Due to the simplified representation of the influences on energy consumption that occur in reality (traffic, gradient, weather, etc. ), these data show a partly, not insignificant, difference to real measured energy consumption data [15; 16]. The concept presented in this paper is to generate realistic routes and realistic driving simulations and to calculate the corresponding energy consumption. A tool is developed for this work which obtains data from APIs that are then used to generate realistic routes. Due to the access to global GPS data, any route can be simulated. Furthermore, by including additional APIs, various data can be collected that have an influence on energy consumption. These include weather data, real-time traffic data, slopes, etc. The second part of the concept focuses on the simulation of energy consumption. For this purpose, the created route data is transferred to a simulation environment. The modular structure of the simulation allows, for example, various vehicles to be simulated on different routes with different driver models. From the route data and the vehicle simulation, the energy consumption can be calculated. The expected outcomes of the simulated energy consumption are (close to) realistic results. The simulation should be able to perform in different setups (same vehicle on different routes) and maintain its accuracy to simulate the respective energy consumption. The objective of this work is to generate realistic energy flows of electric vehicles with a hybrid energy storage system using a model-based approach. For this purpose, whitebox models of the vehicle components relevant for us (powertrain, battery, supercapacitor and DC/DC converter) are created and implemented in a simulation environment with further blackbox models to form a complete vehicle.