# Development of a Hybrid Electric Vehicle Simulation Tool with a Rule-Based Topology
## 3 Results
### HEV Simulation Results
#### 3.1.2 Optimization of Elements  
After the validation of the vehicle model, a method for optimization is required for hybrid systems to improve their energy consumption or driving performance on the basis of the driver's requests. The role of the optimization method is not only to find optimal selections and boundaries of the working modes, but also to enable the user to have an idea of the optimal design of hybrid configurations and components under the given driving conditions. Through the combination of the hybrid with an ICE, the engine and the EMs mainly run at the maximum feasible efficiency operating point within the driving cycle. The user has to consider the power limit of components and the SOC of the battery. For this reason, the selection of the number of years and the type of transmission play a very important role. As described in Section 2.3.1, the GS algorithm is used as the optimization method because the traditional control strategies and optimization tools used in the HEV simulation are a black box. The hybrid simulation is able to perform optimization tasks to determine the maximum potential of a given architecture, and then, on the basis of the simulation results, the user is able to start the next initial optimization step with backward optimized result for parameter estimation, component selection and parameter tuning. By repeating the simulation steps, the GS algorithm is able to determine the best solution for the parameters by defining the recursion equation. This can be used to find optimal solutions in applications such as portfolio optimization, resource allocation, and production planning and scheduling. For this reason, the GS algorithm is used to improve the overall performance by adapting rule-based topologies (Appendix A). Figure 8 shows the WLTC operating point distribution of the engine (1.6 L CI engine) for a parallel hybrid and a serial hybrid. From the first simulation, the average ICE efficiency was about 33%, which is a relatively high efficiency compared to conventional vehicles without hybridization. However, the efficiency can be further improved by shifting the operating conditions in the optimization process, as the area of high engine efficiency is located at high engine load for the ICE. By adapting the gear ratios and the mode switching (the optimization function of the power split), a mean engine efficiency about 2% points higher was achieved using the GS optimization process. The target of minimizing fuel consumption was the main request for GS optimization, while also maintaining the same SOC between the SOC_initial and SOC_final during the driving cycle. In a similar way, the EMs and other components can be also optimized by means of this process. Figure 8: Operating point distribution of the ICE for a parallel hybrid and a serial hybrid on WLTC (1.6 L CI engine). The selection of components is important for the hybrid model, because the operation points have to be selected with respect to the limits of components and the size of materials, which are linked to the cost of the vehicle. The simulation can be used for the adaptation of such hybrid components, e.g., EMs, generators, batteries, and gear sets. From the first simulation, the mean efficiency of the EM (80 kW) for a serial hybrid on WLTC was about 87.8% (83.4% with an inverter). In the optimization process, the adapted axle drive ratio was checked, including the possibility of changing the transmission ratio. On the basis of this process, the mean efficiency of the EM was able to reach up to 90% by adapting the efficiencies required for WLTC. The improvement is mainly a result of shifting to the high-efficiency area by means of the adaptation of the components and the gear set. This value could be even higher by adapting new components and using exemplary inverters with higher efficiency traction. Figure 9 shows the final energy-weighted operating points of the EMs (80 kW) for a serial hybrid on WLTC. By means of the optimization process, the mean efficiencies of the EM were able to reach more than 92%.