# Concept for Generating Energy Demand in Electric Vehicles with a Model Based Approach
## 2 State of the Art  
Currently, several approaches to model a holistic vehicle for energy flow simulation exist. In [2], the models used to determine energy consumption are divided into three categories. These include a physical model, which is derived from physical relationships and described by using analytical equations, an energy model and a state of charge (SoC) model. The physical model in this work is based on [PERSON]'s laws and uses various variables of the vehicle as input (e.g., vehicle mass, frontal area, rolling resistance, etc.). The energy model and the state of charge model, on the other hand, take the energy and SoC values at the start and destination points, respectively, and the distance traveled as computational variables. To calculate the energy consumption, on the one hand a trip with constant speed is simulated, and on the other hand, a driving cycle with start/stop scenarios is used. For the simulation, it is assumed that the route geometry as well as the speed profile must be completely known in advance.  
A similar approach is described in [9]. In this work, [PERSON]'s laws are also chosen as the basis of the physical model. Furthermore, three different driver models are presented here which are respectively designed with a P, PI and a PID controller. At each simulation step, the driver model now compares the vehicle speed with the speed profile of the driving cycle and gives an acceleration or braking signal based on the difference. The NEDC and WLTP driving cycles are used here for the simulation. Similar to [2], this work also assumes that the speed profile is fully known. Since energy consumption models with hybrid energy storage systems are part of the current state of research, they were also considered in the following. In [17; 18], the physical model is divided into different submodels. For the energy storage devices, both a supercapacitor model and a battery model are created. These are implemented based on equivalent circuit. As in [2], no driver model is used, but standard cycles like the Artemis Urban (AU) cycle, the New York City Cycle (NYCC) and New York Composite Cycle (NY Comp) are used for the speed profile.  
The approach of [19], like [2; 9], also uses [PERSON]'s laws as the basis for the physical model. For the simplified modeling of the HESS, it is assumed that the battery, the supercapacitor and the electric power have constant energy transmission/conversion. In contrast to the presented approaches, the data set of a real test drive is used as a speed profile. These data are much more realistic than the previously used standard cycles but have the quantitative disadvantage that only one simulation can be made because only one data set is available.  
The approaches presented mostly use simplified vehicle models without the possibility of being able to fully control or regulate the energy storage system during the simulation. In addition, the standard cycles used for most projects mean that a previously defined speed profile is used for the simulation and that these only reproduce reality to a limited extent [15].