## 1 Introduction
Along the same line, ECMS approaches have been proposed that rely on considering instantaneous SoC values to be used as state feedback to control the battery SoC variation for charge-sustaining [22; 23; 24]. In contrast to the above-mentioned studies, researchers have taken investigations to a next level by carrying out experimental examination of EMSs through HiL tests to address their real-time performance and applicability. However, among these studies, many have been limited in terms of including testbeds that can represent a drivetrain architecture in a high-fidelity manner. In other words, in these test benches, fast prototyping of equivalent drivetrains by using hardware-based simulators/interfaces were considered instead of including mechanical (e.g., rotatory machines) and electrical (e.g., battery, inverters, and converters) prototyped components. For example, in [8], a HiL  
Figure 1: The “V” development process composed of various testing phases. test system without prototyped components and based on a standalone dSPACE and control desk was employed to verify the real-time capability of an ECMS-based approach versus the simulation results proposed for a hybrid city bus. In another study, the typical control strategies of two passenger HEVs, a Jeep Commander and Toyota Prius, were tested through a university HiL testbed with limitations on the maximum torque and speed measurement [25]. In that test bench, the objective was to combine relatively low-cost off-the-shelf products to examine the test environment and realize phases of real-time data acquisition, signal generation, automatic code generation, and power measurements using MATLAB/Simulink(r), dSPACE, and a Hioki power analyzer. The applicability of combining RB and OB EMS control were proposed in [26], while the experimentally-determined parameters of the components were considered instead of real drivetrain components for considering motor/generator dynamics and battery. [PERSON] et al. [5] performed a HiL analysis for EMS of a parallel HEV by a rapid prototyping approach. They investigated low-level ECUs coupled to a dSPACE HiL simulator to virtually capture and actuate signals for the engine and motor's torque-speed operating pairs over a full driving cycle. [PERSON] et al. [27] combined embedded and software-based simulations to verify the feasibility of a HiL methodology for a supervisory control downloaded into a midsize HiL machine including a load emulator card. This semi-physical study was performed based on a practical application of dSPACE products to provide ECU development as a progress phase. In that study, it was reported that including other physical units to their test bench was required for further realistic verification tests. The components of a series-parallel hybrid electric city-bus were modeled in MATLAB/Simulink(r) by [PERSON] et al. [28] and its EMS was tested. In that study, a commercial HiL simulator, PT-LABCAR, in the presence of a real control unit, were used, while the engine, motor. and battery were emulated in a software-based manner. To verify the control, the actual and setpoint speed of the final drive were compared. However, similar comparisons are essential for other crucial features (i.e., torque and rotational speed) to confirm the controllability, power sharing competency, and actuation response of an EMS in a more comprehensive way. The torque and speed of the engine and motor obtained from the HiL and MiL tests were compared for real-time verification of EMS control for a GM Chevrolet Volt case study by [PERSON] et al. [29]. The objective of their study was to validate the physical control signals generated by EMS while the components were emulated by mathematical models. In that study, a low-level simple HiL test bench including a TI controller and oscilloscope were used where Typhoon HiL, aside from the PSIM software environments, were used as the interface and model generator, respectively. [PERSON] et al.