Energy-driven scheduling algorithm for nanosatellite energy harvesting maximization

Slongo, Leonardo Kessler; Martinez, Sara Vega; Eiterer, Bruno Vale Barbosa; Pereira, T.G.; Bezerra, Eduardo Augusto; Paiva, K.V.

doi:10.1016/j.actaastro.2018.03.052

Cited by 26 publications

(25 citation statements)

References 15 publications

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“…A recent work shows how to achieve energy harvesting maximization with this architecture, by controlling the load power consumption (energy-driven satellite tasks execution). 43 From figures Figures 38 to 40, one may also note that the VLDO output voltage clamping impaired its energy harvesting performance. As mentioned before, this has occurred due to the current dependence in the clamping state.…”

Section: Resultsmentioning

confidence: 99%

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Nanosatellite electrical power system architectures: Models, simulations, and tests

Slongo

Martinez

Eiterer

et al. 2020

Circuit Theory & Apps

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KESSLER SLONGO ET AL. power point tracking (MPPT) techniques, high-efficiency solar cells, and energy-aware scheduling algorithms are some of the hot topics under research nowadays. Due to size restrictions and aiming low complexity in design, many nanosatellite designers adopt the direct energy transfer (DET) architecture. KySat-2 is an example of a successfully accomplished mission, based on this EPS topology. Designed by Morehead State University Space Science and Engineering group, KySat-2 EPS was powered by a set of gold-plated deployable solar panels with 26% of efficiency. It provided four high-power regulated rails (two 3.3 V and two 5 V) and a low-noise, low power 3.3V rail for noise-sensitive devices. The energy storage system was made of three 18650 lithium-ion cells connected in series, and the high-power rails reached efficiencies approaching 90%. 12,21 Aiming minimum space occupation and low power consumption, the EPS proposed for the AraMiS project has a boost regulator operating the solar panels close to their MPP. 16 In order to reduce the number of components, the designers opted by the constant voltage MPPT algorithm, using only analog devices. The EPS steps up solar panels voltage from 4.4 V to the distribution bus voltage level (14 ± 2 V). It provides power buses with 3.3 and 5 V voltage levels. The EPS efficiency analysis is demonstrated, calculating the main components power losses. Although this is a very detailed and well-described work, it does not compare the proposed solution with other EPS architectures. A 3U EPS efficiency analysis is presented by Gonzalez-Llorente et al. 22 The subsystem is based on a buck converter that steps down the solar panels voltage (15 or 7.5 V) to the litChium-ion battery range of 3.3 or 6.6 V. The authors define an optimum operation point for the DC-DC converter in order to achieve its maximum efficiency. The operation point is defined by the converter input voltage, output voltage, and output power. Therefore, the discussion is based on different solar cells connections configurations, and battery cells arrangement, that result in the most efficient EPS configuration. Different scenarios have been analyzed to achieve 98% of peak efficiency on the best configuration: input voltage of 7.4 V, output voltage of 3.3 V, and output current varying from 0.1 mA to 2.1 A. Only the buck converter topology is discussed in this paper, and it does not consider any MPPT technique. An interesting solution adopted for the ERPSAT-1 picosatellite uses fuzzy logic to obtain energy harvesting maximization. 23 The developed subsystem has three main blocks, which are the fuzzy maximum power point tracker, the power conditioner, and the hierarchical fuzzy subsystem controller. The fuzzy logic algorithm has been implemented in a dedicated microcontroller that controls a boost converter. Simulations have been performed to demonstrate the better efficiency of the proposed method when compared to the Perturb and Observe MPPT algorithm. Although a comparison is provided in this work,...

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Section: Resultsmentioning

confidence: 99%

“…The battery voltage dependence may be used to maximize the solar panels power input by controlling the satellite tasks execution. 43…”

Section: Directly Coupledmentioning

confidence: 99%

Nanosatellite electrical power system architectures: Models, simulations, and tests

Slongo

Martinez

Eiterer

et al. 2020

Circuit Theory & Apps

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“…The directly coupled architecture is a DET topology, which is the simplest energy harvesting model [24]. Figure 5 shows a simplified directly coupled circuit diagram, where it has a single block representing solar panels.…”

Section: Electrical Modelmentioning

confidence: 99%

“…The diode current is expressed by Equation (45) [24], where I S w is the saturation current, η w is the ideality factor of the diode, k being the Boltzmann constant and q the charge of the electron.…”

Section: Solar Panelmentioning

confidence: 99%

“…On the other hand, the work of [7] studied the state of charge estimation for the battery of satellites, but the authors did not assess it considering typical transient irradiance and temperature profiles found in orbit. There are also papers in the literature concerning specifically the design and management of satellites' power systems (electrical models) [20][21][22][23][24][25]; however, they do not present any generalized method that CubeSat engineers can further develop in order to satisfy the mission constraints and requirements that they are focused on in that moment.…”

Section: Introductionmentioning

confidence: 99%

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An Integrated Thermal-Electrical Model for Simulations of Battery Behavior in CubeSats

et al. 2021

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This work presents an integrated thermal-electrical simulation model, capable of taking into account the thermal and electrical effects of the battery and photovoltaic panels for each instant of time in a given orbit and attitude. Using the physical equations that govern the thermal and electrical models involved during a CubeSat operation, the proposed integrated model can estimate the temperature and energy conditions of the battery, not only in an isolated way but also in considering the mutual effects on the system. Besides, special attention is given to photovoltaic panels used in the energy harvesting process, whose performance is affected by irradiance and temperature along the orbit. The integrated model can be useful for engineers when developing the subsystems of their CubeSats, taking into account, for example, the battery temperature control through a heater. Simulations were performed to illustrate the functioning of the proposed model with variations in the power requirements of its modules and the temperature of the battery throughout the orbit, and a heater’s influence on it.

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On‐board energy scheduling optimization algorithm for nanosatellites

Martinez

Seman

Filho

et al. 2023

Circuit Theory & Apps

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SummaryThis work proposes a real‐time and online energy scheduling optimization algorithm for nanosatellites operating with a direct energy transfer (DET) architecture. The goal of the algorithm is to optimize energy utilization by maximizing energy harvesting, meeting task deadlines and priorities, and ensuring a minimum quality of service (QoS) for the system. The algorithm is composed of a modified perturb and observe algorithm to reach the best energy efficiency point of the solar panels, a task prioritization algorithm to guarantee their times and minimum QoS, and a backpack optimization problem to maximize the energy efficiency of the satellite. To demonstrate the effectiveness of the proposed algorithm, simulations of a nanosatellite operating in a given orbit, attitude, and thermal parameters were conducted and compared to other task scheduling strategies. The results showed that the proposed energy scheduling algorithm had the best performance in terms of energy balance and average power consumption, with an energy balance up to 16% higher compared to the other tested strategies. This demonstrates the ability of the proposed algorithm to optimize power consumption and energy utilization, as well as efficiently schedule tasks to maximize energy harvesting. The proposed energy scheduling optimization algorithm has the potential to be a useful tool for the design and optimization of future satellite missions and could potentially guide the design of electrical power systems for new CubeSat missions operating with a DET architecture. The algorithm's ability to optimize energy utilization and ensure a minimum QoS for the system could improve the overall efficiency and performance of the satellite.

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Energy-driven scheduling algorithm for nanosatellite energy harvesting maximization

Cited by 26 publications

References 15 publications

Nanosatellite electrical power system architectures: Models, simulations, and tests

Nanosatellite electrical power system architectures: Models, simulations, and tests

An Integrated Thermal-Electrical Model for Simulations of Battery Behavior in CubeSats

On‐board energy scheduling optimization algorithm for nanosatellites

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