Energy Management of an Aircraft Electrical System

ENIGMA—A Centralised Supervisory Controller for Enhanced Onboard Electrical Energy Management with Model in the Loop Demonstration

“…For the optimization, P E (t), P I (t), and P A (t) are considered as the optimization variables while T s , P E , P E , SOC E , SOC E , CAP E , P I , and P I are known parameter values provided offline, and δ E (t) and δ I (t) are the online measurements made available from ESRS and PLB1 SDU, respectively, at each time instant t. The CSS OP, as shown in (10) and (11), is a mixed-integer linear programming (MILP) and can be solved using state-of-the-art MILP solvers. The OP is solved at each time instant t based on the system measurements and the known system parameters.…”

“…Assumption 2 provides information about the set point of for the SGN, which is P A (t) = 0. When the PLB1 SDU is activated, the objective function (10) and constraint (6) are considered along with the aforementioned parameter settings for P E (t) and P A (t). Equation (10), when solved for P I (t) and then substituted in (6), produces the following inequality: max P I , δ g1 (t) • P g1 (t) + δ g2 • P g2 (t) − P THy − P E (t) • δ I (t) ≤ P I (t)…”

“…According to the literature, energy management schemes mainly involve the efficient management of energy storage devices [6][7][8][9][10][11] and the management of loads, including E2-EM overcomes this fundamental limit of simple ELM and instead considers an advanced smart control of aircraft electrical loads and power sources rather than just ON/OFF actions. This is achieved by the following two features:…”

“…According to the literature, energy management schemes mainly involve the efficient management of energy storage devices [6][7][8][9][10][11] and the management of loads, including priority-based load shedding [2,12,13]. Furthermore, the idea of extending the energy storage and load management techniques to eliminate the overload capabilities of a generator has been considered by researchers and engineers due to its obvious operational and environmental benefits and the inclusion techniques to manage overload through generators [14], batteries [6], supercapacitors, and power distribution to loads [14].…”

Application of Multiphysical Domain Modeling in Electrical System Simulation

“…e electrical equipment operation of the more electric aircraft involves the transmission, interaction, and conversion of the multiphysical domain, such as electrical energy, mechanical energy, hydraulic energy, thermal energy, and information [7,8]. Since the conversion process is dynamic, it is obviously inaccurate to discuss the energy utilization performance simply by using device efficiency, and a digital simulation method is needed [9,10].…”