**7. Driving Cycles Testing**

The complete development and simulation of the ORC system model provided useful data regarding the efficiency and fuel consumption of the new, improved powertrain. This fact enables a comparison to be made between the initial engine setup and the new, improved one. The best way to compare these two powertrains is to assign them to a conventional lightweight vehicle and test them for various driving cycles. In this way the percentage difference between these two powertrains can be obtained, showing how much difference the ORC system produced. The fuel consumption benefit was the main target of this assessment, but emissions were also computed, and the major concern of this study remains the minimization of the fuel consumption of a lightweight passenger vehicle with the use of an ORC WHR recovery system.

With the use of three typical driving cycles, the fuel consumption of the initial powertrain and the powertrain with the ORC system was measured to define the extent that the ORC system benefits the vehicle. The driving cycles include:


All of these driving cycles represent different driving scenarios, different durations, and average speeds. In this way, the comparison between the two powertrains (the original standalone hybrid and the hybrid powertrain equipped with the ORC WHR system) is fair and also shows where space for improvement exists if the ORC system is to be implemented in a HEV vehicle. When the developed ORC system is assigned to a HEV vehicle, different hybrid driving modes can be selected for further improved fuel economy in each driving cycle, regardless of the configuration of the HEV vehicle (series, parallel, or complex). These tests were run in GT-Power, where a virtual vehicle was modeled with an average weight of 1500 kg and several parameters set to simulate the driving scenarios. The library of the software includes all of the selected driving cycles, which ensures the precision and consistency of the results. The complete model for this test includes several parameters that were calibrated to achieve a model that fulfilled the requirements of the simulation, which is shown in Figure 4b.
