## 2 Materials and Methods
### HEV Simulation Overviews  
A simulation tool developed on MATLAB(r) and Simulink(r) was used in this study to address the positioning of the GCI technology with hybridized powertrains to meet the future CO2 demands, and it was sufficient enough to give an assessment of the potential of the proposed technology. The vehicle considered for the simulation was a typical medium-sized European C-segment passenger car with the highest demand of all of the vehicle categories in Europe. The vehicle parameters were 1500 kg for the vehicle weight without a battery, 0.3 for the cw-value, 2.28 m\({}^{2}\) for frontal area A, and 0.230 m for the dynamic wheel radius. The weight of the battery was 14.4 kg/kWh. The engine data used for the \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Fuels** & **Diesel** & **CN15** & **CN25** & **CN35** \\ \hline CN (-) & 53 & \(\sim\)15 & 25 & 35 \\ RON (-) & - & 90 & 70 & 45 \\ T10, T50, T90 (\({}^{\circ}\)C) & 210, 105, 335 & 25, 105, 151 & 53, 103, 160 & 74, 104, 164 \\ H/C ratio & 1.85 & 1.8 & 2.00 & 2.14 \\ Viscosity (mm\({}^{2}\)/s at 40 \({}^{\circ}\)C) & 2.67 & 0.47 & 0.60 & 0.53 \\ Density (kg/L at 15 \({}^{\circ}\)C) & 0.834 & 0.749 & 0.736 & 0.726 \\ LHV (MJ/kg) & 42.7 & 42.8 & 43.2 & 43.8 \\ Aromatics (v\%) & 25 & 26.8 & 16.4 & 5.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of fuel properties. \begin{table}
\begin{tabular}{c c} \hline \hline
**Engines and Nozzle Geometries** & **Single- and 4-Cylinder Engines** \\ \hline Displacement Volume (L) & 1.560 (4-cylinder engine) \\ Bore (mm) \(\times\) stroke (mm) & 75.0 \(\times\) 88.3 \\ Compression ratio (-) & 16.0:1 \\ Swirl number (-) & 2.0 \\ Hydraulic flow (cc/30 s, 100 bar) & 280 (diesel)/340 (CN fuels) \\ Nozzle holes (number) & 7 \\ Fuel pump (-) & Bosch, CP1h \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Specification of engines and nozzle. simulation was the GT-Power engine simulation results based on the test results of other GCI studies. The aim of vehicle electric hybridization is to improve energy conversion efficiency by supporting the engine during the peak load and then to reduce emissions such as CO\({}_{2}\). In addition, the implementation of an electric motor (EM)/generator (Gen) creates new capabilities such as full electric (EV) mode and regenerative braking. The calculated total forces are given as the input to the ICE model in the case of a conventional vehicle model. In a hybrid vehicle model, additional blocks such as EMs and a supervisor are also implemented. The supervisor will direct the power demands to ICE or Ems depending on the operating points and the strategy. The control strategy of the supervisor is the most important thing in any model, and the system behaves according to the strategy defined by the user. This is nothing but the supervisor in the hybrid powertrain, which is also known as the brain of the system. The rules of the supervisor are to:  
* Continuously meet the driver's power requests based on the accelerator and brake pedal positions and the available power in the power sources;
* To minimize the global fuel consumption;
* To maintain state of charge (SOC) of the battery between the bounds of the defined SOC;
* To make sure that the battery SOC at the end of the driving cycle reaches the user's request. For the control system to switch from one transition to another, certain conditions had to be defined from which transitions from different states were possible. The control system contains logic functions, and based on this, the switching takes place; this is the case for all possible cases in the control system. Once the conditions are defined, it was integrated with the other inputs for the conditions to work by integrating all of these the control system parameters.