## 1 Introduction  
Due to the electrification of transportation for human society, it is forecasted that the transportation sector will account for a significant share of society's energy demand in the future. Recent statistics clearly indicate a rapid increase of plug-in hybrid electric vehicles (HEVs) and battery-powered electric vehicles (BEVs). In the future, connected and autonomous vehicles (CAVs) will also need to be charged by the electricity grid; thus, they will increase the loads and challenges for smart grids [1; 2; 3]. When conceptualizing future transportation, the energy demand of the type of transportation needs to be taken into account. Forecasts indicate that society's energy consumption will increase by 56% between 2010 and 2040 [4]. Even though new propulsion and driving technologies are being implemented in new automobiles, for charging plug-in HEVs, BEVs and CAVs, the vast majority is produced by non-renewable resources, such as coal, oil, gas and nuclear power (COGN) energy sources [5; 6]. Overall, estimations show that global energy-related carbon dioxide emissions by human society will increase to 45 billion metric tons by the year 2040, representing an increase of 46% compared to 2010 [4]. Solar energy has been identified as one of the most promising candidates to help withdraw from the dependency on COGN energy sources [6], and it can be used for large-scale and small-scale energy production [7; 8]. Hence, solar energy provides the opportunity to produce the required electricity for plug-in HEVs, BEVs and CAVs. More precisely, photovoltaic (PV) cells can be integrated into the roof and other surfaces of electric vehicles in order to provide electricity for the onboard power supply and to extend the electrical driving range (ERE) [9; 10]. Likewise, PV charging stations can be implemented for charging the high-voltage batteries of BEVs, for example [7; 11; 12]. When integrating PV cells into the surfaces of electric vehicles, these types of vehicles can be turned from consumers of electricity from the power grid into producers of energy for the grid [9]. There is an opportunity to produce PV energy under parking conditions, as well as driving conditions [13; 14; 15]. In this way, the contribution of electric vehicles to the pollution of the environment can also be reduced [16]. Statistics show that in 2015, 950 million vehicles for individual transportation were in operation. Statistics also show that the number of passenger vehicles is increasing at a steady rate every year [17]. Hence, the research and development (R&D) questions that arise when trying to integrate PV cells into electric vehicles in an efficient way must be addressed [16]. At present, PV energy production in electric vehicles represents a new area for this type of resource [10; 16]. Hence, as with other new application fields for energy resources, the given environmental conditions have to be studied and investigated. More precisely, it is crucial to understand the behavior and fluctuations of the available output current and power of PV cells due to changes in the available irradiation [18]. Furthermore, the potential contribution of vehicles' PV installations to the overall electricity demand can be calculated. Here, PV simulation models can help to predict the possible extension of the ERE of electric vehicles. Recent research indicates that, depending on the size of the PV installation and the environmental conditions, about 70% of a vehicle's electricity demand can be met with PV energy [16]. The single-diode model is used as an equivalent circuit to model single PV cells and panels [8; 19; 20; 21]. The accuracy of the PV simulation model depends on two tasks. First, unknown model parameters have to be calculated and estimated. In this way, the error between real and simulated PV cells should be as small as possible [19; 20; 21; 22; 23]. Second, it has to be taken into account that the environmental conditions have a direct impact on the obtainable output current, and thus the potential output power of photovoltaics.