Efficiency Focused Energy Management Strategy Based on Optimal Droop Gain Design for More Electric Aircraft

Due to the substantial increase in the number of electrically driven systems onboard more electric aircraft (MEA), the onboard electric power systems (EPSs) are becoming more and more complex. Therefore, there is a need to develop a control strategy to manage the overall EPS energy flow and ensure the operation of safety-critical systems (which are electrical loads) under different operating scenarios and to consider EPS losses minimization, exploiting the thermal capability of generators, different load priorities, and available batteries with their charging and discharging schedules. This article presents an energy management (EM) strategy that considers the aforementioned objectives. The optimal droop gain approach is employed as a power-sharing method to minimize the total EPS losses in MEA. A finite state machine (FSM) has been used to implement the control strategy to realize the EPS reconfiguration operation. The proposed EM strategy is implemented and simulated using MATLAB/Simulink and hardware-in-the-loop (HIL) under different operational scenarios, such as normal operations, failure of one of the power generation channels, and failure of all power generation channels. The proposed EM method has shown its capability to efficiently manage the EPS under different operating conditions to reduce the overall system losses.

the electric power system (EPS) in terms of power generation, transmission, and distribution [4]- [7]. The four typical EPS architectures for MEA are constant frequency ac EPS, hybrid ac and dc EPS, hybrid high-voltage (HV) ac, HVdc EPS, and pure HVdc EPS [8]. Pure HVdc topology mainly distributes power in dc form, and it is considered a very promising architecture for future MEAs [9], [10]. As the demand for electric power onboard modern aircraft rises dramatically, the low maintenance and high EPS reliability are essential for the design of future MEA. The 270 HVdc EPS concept is now considered an optimal option for future aircraft due to its relative simplicity, flexibility, and unique ability of dc systems to supply uninterrupted power to electrical loads [11], [12]. One of the possible HVdc EPS architectures is shown in Fig. 1; the generators with corresponding active front-end (AFE) converters and batteries with corresponding bidirectional dc/dc converters are connected to the 270 HVdc bus by solid-state power controllers (SPPCs) C1-C3, C10, and C11. These types of switches are used for communication of the EPS, as well as to control the power flow and reconfigure the topology of the EPS by creating new connections between EPS elements. Different system reconfigurations can be obtained by changing the status of the circuit breakers (open/closed). For example, when one of the power generation channels fails, the auxiliary power unit (APU) or battery system may be used to supply some emergency buses to enable safetycritical operations. The energy management (EM) strategy is required to manage the power flow distribution and EPS reconfigurations, setting a new power path and ensuring safe operation under different operating scenarios. The power distribution is a remote distribution, as shown in Fig. 2, which means the power generated and distributed efficiently near to its consumption and is divided into three stages, i.e., power generation, primary power distribution, and secondary power distribution. At the power generation level, there are two main permanent magnet machines (PMMs) driven by one engine that works as a starter/generator (S/G) and one APU, all interfaced with 270-V single dc bus through AFE converters. The APU is used as a backup power source during flight and provides power to the power users during ground operations, which makes the airplane electrically self-sufficient on the ground. The AFE converter controls the speed and the dc bus voltage of the S/G PMM during starting and generating modes, respectively, besides other functions, i.e., overvoltage protection, parallel generator operation, and others. There are four different voltage buses at the primary power distribution stage to supply different loads types, namely, variable frequency 115/ VAC, constant frequency 115 VAC/400 Hz, and 28 VDC, besides 270 HVdc. The conversion to different operating voltages to drive all of the onboard loads' types is performed using the power converters. The authors in this study used the available loads' analysis data for the Flying Crane aircraft. Flying Crane is a medium to short-haul aircraft with 130 seats, which is mainly aimed at the Chinese domestic air transport market. Also, it is considered to be a competitor of the current B737 series and A320 series aircraft [12]. The secondary power distribution system includes six Electric Load Management Centres (ELMCs) to deliver and manage power to the loads, as shown in Fig. 2. In terms of emergencies, the EPS relies on power from two Li-ion batteries. These batteries are used to provide emergency power for the high priority loads, when faults occur in a flight, and for starting the APU. The Li-ion is chosen because it has the right functionality and chemistry to deliver a large amount of power in a short time. HV distribution is recommended to reduce the size of conductors and power losses of the system. To realize a stable and reliable flight mission and improve the energy efficiency of MEA, an EM strategy is used.

A. Typical Implementation of Energy Management
In today's aircraft, electric load management (ELM) based on fixed priorities of loads is often implemented [13]. The loads can be shed and reconnected depending on their importance during the flight. There is often a fixed, predefined priority for each controllable load, and the higher priority load will be shed later. The powers of the generators and the loads are measured to determine the number of loads to be shed. Often, a set of similar loads are connected to one switch [13]. In the case of many loads with the same priority, the ELM uses additional criteria to determine which loads are shed and which are not. One solution is to shed the large loads first; this keeps as many loads as possible connected. Another solution is to find a set of loads that consume as much as possible of generator capacity, and this is called the "Knapsack problem" [13]. The advantages of the ELM strategy are a simple basic implementation, just defining the priorities for each load and thresholds at which shedding and reconnection take place, and that proven and mature algorithms are available for it since it has been applied for decades. Regarding the disadvantages, ELM is limited to switchable loads in most cases and cannot deal sufficiently with continuously controllable loads. The priorities of loads are may not be fixed during flight, these can depend on the flight phase and other conditions, and this is not considered by the typical ELM. Furthermore, ELM is not capable of optimizing the system efficiency or reducing the size and weight of EPS.

B. Energy Management Strategy
The goal of an EM strategy is to ensure the stability and quality of the EPS network by managing power flow while respecting nominal operating points and avoiding unfavorable conditions of usage, i.e., high cycling rates for batteries or high dynamics power demands for generators [14]. Moreover, during the development of EPS EM strategies, the safe operation of the EPS is another critical factor to consider. By designing the right EM strategy, the system weight is minimized; hence, the overall efficiency is improved. Furthermore, a properly designed management strategy provides the potential for the aircraft to operate at its maximum performance under fault conditions. To achieve these aims, the controller can be given the task of reconfiguring the system by switching ON or OFF a number of circuit breakers based on the reconfiguration strategy [15]. The reconfiguration approach is utilized to find the correct power path for each load to be fed by using switches while considering the optimization of the system in terms of power flow and avoiding unsafe configurations [16], [17]. The EPS is managed by the control system in order to maintain an uninterruptible power supply for loads. However, rules must be defined to avoid unsafe conditions, such as creating parallel power paths between two sources or discharging the batteries beyond a preset limit.
In [15], a control strategy to manage the power flow in the EPS and ensure continuous power supply to the high priority loads under different power converter failures for MEA is presented. The proposed strategy is applied through a smart controller, and the control logic is implemented using the finite state machine (FSM) approach. The actions taken by the controller under different operating conditions are dependent on the State of Charge (SoC) of the batteries. In [18], the balance between the aircraft power supply (gas turbine generator and storage device) and power demands, while minimizing the operation cost including fuel and battery operation cost, is formulated as mixed-integer nonlinear programming (MINLP) power management problem for MEA civil aircraft. The outputs of MINLP are optimal active power generation, load management, and battery charging/discharging status. In [19], a power allocation and load management method to minimize the load shedding is presented. The management problem is formulated as the mixed-integer quadratic problem (MIQP) where the decision variables are the generator output power, load connections, and battery charging schedules.
The controller that performs different functions of EM strategy, such as providing uninterruptible power and ensuring safe operation of the EPS, can be implemented using different methods, e.g., FSM. The FSM method is a way of formalizing the logic of a controller, where the controller is considered to be in one of a set number of states and will transition to other states (or the same state) during its operation, potentially setting some outputs as a consequence of the state that it is in or the transitions that it performs. When linear temporal logic (LTL) is used to specify a controller, a "controller synthesis" step is usually performed, whereby an FSM is automatically generated from the LTL formulation. However, it is more common to generate an FSM manually and for many years, it has been considered a suitable tool for the control logic design of EPS management, as well as being applied to model problems in many other areas, including mathematics and artificial intelligence. FSM is a computation model that can be used to simulate sequential logic and can be implemented with hardware or software. In FSM, it is possible to model the behavior of the system as a set of states and transitions between states, which are known as reactive systems [20]. The advantages of using FSM for controller design are that it is easy to use and visualize, and formulations already exist for many powerful and fast algorithms [15].
To the best of the author's knowledge, there is a lack of research conducted in the area of proposing an intelligent EM strategy to ensure uninterruptible power supply to safety-critical loads and considering system losses minimization (converters and transmission lines losses), exploiting the thermal capability (overload) of generators, and considering variable load priority during flight phases and schedules of batteries charging/discharging, to supplying safety-critical and noncritical loads during different failure scenarios. The main contributions of this article can be summarized as follows.
1) Proposing a smart EM strategy, which ensures that the safety-critical loads are powered under different flight scenarios by reconfiguring the EPS. Furthermore, the proposed EM considers the exploitation of the generator's thermal capability, variable load priority, system losses minimization, and battery charging/discharging schedules. 2) Utilizing the FSM approach to implement the proposed EM strategy logic in the controller as it is easy to use and visualize, and contains fast and powerful algorithms. The rest of this article is divided into four sections as follows. Section II presents the load analysis required for system components sizing and loads priority setting. Section III shows the proposed EM strategy and state transition between different operating scenarios and corresponding system switches and variables' settings. Section IV shows the validation of the proposed method. Finally, Section VII presents the conclusion.

II. LOAD ANALYSIS
The first step of EPS design is to understand the electric load requirement as the EPS aims to provide electric power to all of the onboard loads. Moreover, the load analysis is important to determine the required generating capacity and the required number of main power sources. It is recommended that the majority of loads should be the same voltage type as the primary source. The authors in this study have used the available report on load analysis for the Flying Crane aircraft [12]. The load analysis must include continuous analysis, 5-min analysis, and 5-s analysis. Due to confidentiality issues, the detailed load information cannot be obtained; therefore, the 5-s analysis cannot be included in this study [12]. All of these loads are divided into different categories based on their functions as follows.  Table I shows the load analysis results for Flying Crane aircraft, including continuous (C) and Intermittent (T) or 5-min loads and divided into LPls, MPLs, and HPLs. The total continuous loads during each flight phase are given with and without the intermittent loads. It should be noted that the environmental control system (ECS) power requirement takes nearly half of the total power required and ECS is powered by 270 VDC. The obtained load analysis data mentioned above is used as a case study to verify the proposed EM strategy. In Section III, the proposed EM strategy is discussed in detail.

III. ENERGY MANAGEMENT STRATEGY
This section outlines the proposed control strategy: as mentioned above, this strategy aims to ensure uninterrupted power to the HPLs. Moreover, the batteries are employed to supply the MPLs during generator failures in addition to their basic functions, such as providing power to start the APU and supporting ground operations (refueling, powering the braking system when the airplane is towed, and so on). Moreover, keep the batteries SoC within the preset values. The assumptions for the EM strategy investigated in this study are given as follows.
1) Electrical loads can be either powered or shed (ON/OFF). Loads can be regulated continuously or intermittently. 2) Generators can operate above their nominal power (10%) for a short time (5 min). This overload capacity can be exploited.
3) The EPS can be reconfigured, using switches, to find the appropriate power path for each load to be fed in different situations. 4) Storage devices can both absorb and supply the referenced power (when available). 5) The APU generator will come into an operation in case of the failure of the one of main generations. The APU generator can run in parallel with the remaining main generator. 6) The APU generator is used to provide power to the power users during ground operation. From the discussion in Section I-B, it can be seen that the EPS is a reactive system, i.e., continuously having to react to external and internal stimuli. Therefore, based on [16] and [21], the use of FSM is considered a solution to improve EPS management. In FSM, the behavior of the system can be modeled as a set of states and transitions between states. From a mathematical point of view, the FSM can be seen as where represents a finite set of symbols, S is a finite set of sates, and s 0 is the initial state, so that s 0 ∈ S, and δ is a state transition function where F is the finite set of final states. An example of the formulation is depicted in Fig. 3.
The following equations describe the system in Fig. 3. The inputs are The states can be expressed as The transition function δ that defines mapping between the Cartesian product of the set of states S and the language symbols into the set of states S is given by For example, if the current state is s 0 and the input is ε 01 , the next state will be s 1 and so on. The final state can be given as Since the theory of FSM has been introduced, it can be applied to the EPS in order to set a management strategy. The operating modes can be divided into five main scenarios and 12 subscenarios based on the status of EPS components, and these modes are explained as follows.  If the overloading time is not reached the limit (5 min) and the batteries have been discharging below SoC min , then the system is in ST9. The health generator is overloaded by 10%. The LPLs, MPL1, and MPL2 are all shad in this state to reduce the power requirements.

A. Normal Scenario
If there is surplus power after shedding, the batteries can be charged.

1) State 10 (ST10) (One Generator and APU Running and Not Overloaded, Batteries Charging, and Loads Unshed):
In this state, the APU has started, and it is similar to the normal scenario (ST1). Therefore, the loads that were shed in the previous scenario get unshed and the EMC will not allow the healthy generator to be overloaded more, and the batteries will charge until SoC max .

1) State 11 (ST11) (Main Generators and APU Fail, and SoC Less Than SoC min ):
In this state, the batteries supply the critical loads only to allow the aircraft to land safely.

2) State 12 (ST12) (Main Generators and APU Fail, and SoC Greater Than SoC min ):
If there is enough power in the batteries, this can be exploited by supplying MPL1 and/ MPL2. Fig. 4 illustrates all the states with a simplified and reduced-scale EPS diagram. The failed elements are marked with red crosses. Fig. 5 shows the EM strategy adopted in this work; the EM strategy covers all operation modes, which includes normal, failure of one power generation channel, failure of both power generation channels, and emergencies case. Moreover, the conditions for transitions between states are explained in Section V-F.
As is clear in the figure, there is a reciprocal transition between the major scenarios, and the directions of the arrows illustrate this. The transition will occur between the main scenario first and subsequently between the inside states. For example, if the system is operating in the normal scenario, and both main generators fail, the EM system will switch to the emergency scenario. There are two states in the emergency scenario, ST11 and ST12, which are selected dependent on the SoC of the batteries. The same goes for the other direction.
The EM system will return to normal operation once the fault has been cleared. However, if one of the main generators fails and the other remains faulty, the EM system will switch to the "one of the main generators failure scenario," and the EM system will start at ST6 and move from and to any state within this main scenario as shown by the directions of the arrows, depending on the specified conditions. However, if the other generator fails, while the APU continues to operate, the EM system will switch to ST2 and begin with the scenario "both main generators fail while APU running." The internal transition is carried out in the same manner as described earlier. While, in this scenario, if an APU fails, it will switch to the emergency scenario, if one of the main generator's faults has been cleared, it will move to the scenario "one of the main generators fail."

F. State Transition
The conditions of transition between different states (summarized in Table II) are defined by the status of generators, overload, and SoC of batteries. Table III shows the status of the generator during different scenarios, e.g., if SG1 and SG2 status is normal, the EPS operates in ST1. Table IV indicates that the status of switches, load shedding signal, overload signal, APU message, reference voltage, and power values are sent to the controllers. The value "0" indicates the switch is OFF (open), and the value "1" refers to the switch is ON (closed). The battery controller switch has four control positions (1-4): dc power, battery terminal voltage, dc bus voltage, and halt, respectively [22]. The charging power P chn is chosen here to be 30 kW for each battery pack and the maximum discharge power P dischn to be 75 kW. The reference voltage for the battery cascaded voltage controller V dcn is set to 270 V. In conclusion, the EPS states for the proposed EM strategy and the implementation of the proposed EM method utilizing the FSM technique have been presented. The criteria for transitions between the distinct states were also described based on the status of EPS variables, such as generator status. The effectiveness of the proposed EM strategy will be verified in Section IV.

IV. SIMULATION RESULTS
This section applies the EM strategy proposed in Section II. The optimal droop gains' design that was developed in [23] is used here as the power-sharing method between sources. This proposed power-sharing approach guarantees that the system losses under different EPS reconfigurations are minimized. The multifunction battery controller introduced in [22] is used to reschedule the charging and discharging of the batteries. The battery controller switch has four positions: 1) dc power control; 2) battery voltage control; 3) dc bus voltage control; and 4) battery halt. The EPS, as shown in Fig. 1, is implemented using a MATLAB/Simulink environment for verification study. The two main generators, the APU, and their corresponding converters are modeled as current sources as, in this article, it is required to control the output current [10]. The average model of the battery converter is assumed, and the loads are modeled as constant power loads. The batteries are used to start the APU, and the remaining SoC of the battery pack is assumed to be 70% after starting the APU. Different scenarios are considered, i.e., 1) normal scenario; 2) one of power generation channels' failure scenario; and 3) both power generation channels' failure scenario. The droop gains' design for EPS with converters of different power ratings and different efficiencies is considered. The EPS parameters and ratings of converters are shown in Table V. The total system losses using optimal droop gain design [23] and conventional droop gain design methods are compared [24]. The optimal and conventional droop gains can be calculated as in (7) and (8), respectively, where R di−opt is optimal droop gain of the i th converter and R esi is the equivalent series resistance representing the copper losses of the converter i [23] R di = V max I cimax (8) where V max and I cimax are the maximum allowable voltage drop and the maximum output current of converter i , respectively.

A. Normal Scenario
In this part of the study, a normal flight operation is investigated with the scenario, as given in Table VI. Figs. 6 and 7 show the simulation results for this scenario. In the beginning, the EMC sent the signals to the ELMCs to connect the ground loads during movement on the ground, e.g., taxiing, landing, and towing; therefore, after starting the two main generators, they share the loads equally. If the SoC of the batteries is below 95%, then the batteries are charged with constant current until SoC max1 , which is assumed to be 80% in this study. The batteries continue charging up to SOC max (95%) with constant voltage. The charging current of the battery according to the manufacturer's specifications is limited by 20 A, and the voltage is 148 V, as shown in Fig. 6(g). After SoC reaches 95%, the EMC stops the charging of the batteries. During the flight, the EMC sends signals to the ELMCs  TABLE II   STATES TRANSITION FOR DIFFERENT SCENARIOS   TABLE III STATUS OF GENERATORS, BATTERIES SOC AND OVERLOADING TIME DURING DIFFERENT SCENARIOS to manage the loads in each flight phase according to the corresponding time, as shown in Fig. 7. It should be noted that the dc bus voltage is kept within the limits of 250-280 V according to MIL-STD-704F [25], as evidenced in Fig. 6(a).
The comparison between optimal [23] and conventional droop gains' designs for the power-sharing between sources is investigated. This comparison considers the total system losses, including converters, transmission lines losses, and battery losses (inductor and internal resistance) during the normal flight. It is clear from Fig. 8 that the optimal droop gains' design provides reduced losses in comparison to the conventional design, and the total EPS losses under conventional droop control are 107 kW, while, under the optimal droop one, they are 94 kW, i.e., they are reduced by 13 kW (or 11.3%) during the flight.    The flight started normally, as both main generators supplied the loads together, in addition to charging the batteries until these reach the maximum SoC value (95%). After reaching the maximum value, the charging will stop. At t = 1600 s during the cruise, a fault in the main generator occurs. The EM responds to this fault by going to ST6 directly. In this state, a signal is sent to the APU generator to prepare to start and share the loads, and the remaining healthy main generator is allowed to overload by 10%. After 50 s, the APU generator is ready to share the loads with the main generator. The overload of the main generator is cleared, and the batteries are charging until they reach the maximum SoC values; this covers ST10. At t = 1900 s, a fault occurs in the APU generator; in this case, the healthy main generator is allowed to overload again, the batteries are allowed to provide 70 kW of power (ST6). As mentioned above, the healthy generator is allowed to overload for a period of 300 s (5 min); at t = 2200 s, the overload period expires consequently, and the batteries need to supply the required power, gradually discharging until SoC drop to its minimum SoC value (ST7). At t = 2665 s, the SoC reaches the minimum values (28%). Therefore, they will start charging after shedding LPLs, and part 1 and part 2 of MPLs (ST8). At t = 3920 s, the SoC reaches their maximum values, and the EMC sends the signal to discharge the batteries (ST7). Such a cycle of charging/discharging will continue until the end of the flight. It is clear from Fig. 9(a) that the main dc bus and local dc buses voltages are kept within acceptable limits. Fig. 11 shows the total system losses during the whole flight using conventional and optimal droop gains [23] methods, and it is clear from this figure that the losses in the case of the conventional method are 218 kW against 209 kW in the case of the optimal design, a reduction of 9 kW (4%) for the optimal design. Accordingly, the method of optimal droop gain design gives fewer losses compared to the traditional method.

C. Loss of Both Main Power Generation Scenario
The performance of the EPS under a failure of both main generators using conventional and optimal droop gains was evaluated as well. This scenario runs through STs 2-5, 11, and 12. Figs. 12 and 13 show the simulation results. Initially, the aircraft flies normally (ST1), and at t = 1600 s, during the cruise, the aircraft loses both main power generators simultaneously. According to the EM strategy, the EMC commands to start APU. Until the APU started, the batteries are given supply to the HPLs, as the only option for the pilot is to do a hard landing (ST12). The batteries' voltage controller is activated replacing the batteries' power control since it is critical to maintain the dc bus voltage at the correct level. After 100 s from sending the command from the EMC, the APU is  ready to supply the loads with overloading allowed along with the batteries, and therefore, all the loads are unshaded (ST2). The total load is 345 kW, and the APU delivers 275 kW; therefore, the batteries supply the difference, which is 70 kW.  At t = 1800 s, the APU also fails, so the EMC sent asks the ELMC to shed all loads apart from only part 4 of MPL and HPLs (ST12). When the SoC reaches its minimum value, part 4 of MPLs is also shad, and only the HPLs are powered until the aircraft land safely (ST11). It should be noted that the two battery systems are discharged with different currents because they have different optimal droop control gains, as shown Switching states, reference battery voltage, APU signals, and overload signals under both power generation channels' failure scenarios.
in Fig. 12(h). At t = 2700 s, the APU is back to work with overload capability, so the available power is 275 kW. Therefore, the LPLs and part 1 of MPLs are unshed, and the batteries are charged (ST5). The overload period is ended at 2900 s, and the EMC goes into ST3, at which point the batteries are supplying the deficit in power between the APU and the loads. Moreover, the LPLs and part 1 of MPLs are shed, as shown in Fig. 13(c). When the batteries are fully discharged (SoC < 28%), the EM moves to ST4, in which the LPLs, part 1, and part 2 of MPLs are shed to allow the batteries to charge. At t = 4430 s, the SoC of batteries are reaching the maximum value; therefore, the system backs into ST3. When the batteries SoC drops below their minimum values, the EMC sheds the LPLs, and part one and part two of MPLs, and batteries start to charge again (ST4). It should be noted that the load current changes according to the loads of each flight phase, as shown in Fig. 12(i). It is clear from the results that the dc bus and local dc buses voltages are kept within the limits during the considered emergency case. The total EPS losses using the conventional and optimal droop gains' designs are calculated during each flight phase, as shown in Fig. 14. These were 202 kW for the conventional method but only 195 kW for the optimal droop gain design method [23]. This leads to a 7-kW (3.4%) reduction in losses in the studied scenario. It should be noted that the losses in some operation modes, i.e., ST3, ST4, and ST11 using the optimal droop gains' method, are higher than the conventional method. This is because the batteries are charged/discharged with different powers and due to using different droop gains. The batteries are charged with constant power/voltage, but they have different SoC, and this leads to the time of charging for batteries pack 1 being longer than pack 2 in the considered case. Moreover, the losses will be slightly higher than the conventional method as the battery   packs are fully charged at the same time. However, in general, the total system losses when optimal droop gains are applied are smaller than with the conventional method if the whole flight is considered.

V. HIL VALIDATION
In this section, the model which used in MATLAB/Simulink is simulated on the Typhoon HIL 604 real-time power electronics emulator to evaluate the performance of the proposed EM control strategy. The setup of the hardware-inthe-loop (HIL) experiment is shown in Fig. 15. The PMSM (operating in generation mode), the battery energy storage systems, and three-phase inverters are modeled in the Typhoon device via the Typhoon software schematic editor. A Texas Instrument (TI) digital signal processor (DSP) (i.e., F2879D control card) is used to implement the EM study and then send the control signals to the system components. The control card and the developed system plant in the typhoon software communicate via the interface board, as shown in Fig. 15. Fig. 16 shows the results when the system moves from normal scenario (ST1) to failure of one of the main generators scenario (ST6). It can be seen that the results are identical to those presented in Figs. 9 and 10. Regarding the system losses, it was found that the reduction in losses was equal to 1418 W (9.4%) in ST1 and 155 W (1%) in ST6 when the optimal droop gain is employed. Fig. 17 shows the results when the other main generator is failed (ST12). In this case, the batteries supply the HPLs and MPL1 until the SoC drops below the minimum value. It can be seen from Fig. 17, the dc bus voltage is kept around the nominal value of 270 V by means of the dc bus voltage battery controller. The system losses were nearly equal when the conventional and optimal droop gains are utilized, and they are equal to 1269 W. The Typhoon HIL simulation results show that the proposed EM control strategy can effectively supply the HPLs and reduce system losses under different scenarios in real time.

VI. CONCLUSION
In this article, a proposed EM strategy to minimize the total system losses and take into account the thermal capability of the power generation sources, batteries schedules, and variable load priority for the representative EPS for future MEA is presented. The control logic of the proposed strategy is implemented using FSM. Moreover, it is tested and verified using different operating scenarios for complete flight, i.e., normal, loss of one of power generation channels, and loss of two of power generation channels using the MATLAB/Simulink and the Typhoon HIL platform. The simulation results show that the controller activates the correct state to always provide safety-critical loads for all fault conditions. Furthermore, it confirmed that the proposed method reduced the total system losses in all studied cases compared to the conventional method. The proposed method keeps the main dc bus and local dc buses voltage within standard limits. Furthermore, the example aircraft can fly safely with one generator during the complete trip using the proposed EM strategy.