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On-orbit manufacturing can reduce the cost and time needed by space exploration missions because in-situ maintenance activities can be achieved without the need for additional launches. Furthermore, recent developments in materials science in terms of better mechanical and thermal performance have allowed this application to become a potential reality. However, the deployment of on-orbit manufacturing presents several challenges, including the lack of convective heat transfer and human intervention. This paper proposes an on-orbit 3D printing device capable of operating at a temperature up to 400°C in the vacuum environment. To validate its feasibility for on-orbit manufacturing, we designed four extruders with different characteristics. We investigated the temperature profiles across the extruders under the vacuum condition through a heat transfer model. Based on the thermal analysis, a thermal control method, which combines the Proportion (P) and Fuzzy Proportion and Integration (Fuzzy PI) strategies, is designed to regulate the 3D printing device operation. With the extrusion rate of 8654.6 mm3 /h and the printing temperature at 400°C, the melting and solidification status of the PEEK (Polyether ether ketone) material is verified.

This research addresses the global Mittag-Leffler stability and synchronization control problems of the fractional-order memristor-based neural network, which more accurately describes physical phenomena than integer-order networks system, and simultaneously exhibits complex dynamic behaviors. Specifically, the difficulties due to the processing of derivatives and inequalities of the fractional-order memristor have overcome these issues via fractional differential inclusion, set-valued mapping, and a new Lyapunov functional. Furthermore, the state feedback controller has been designed to flexibly solve the complex system external disturbance, which involves a generalized type of proportional time-delay control law that enables flexible parameter adjustment.Obtained the results demonstrate better exponential stabilizable and asymptotic synchronization over traditional integer-order neural networks. They are also a generalization and promotion of the predecessors on the dynamic behavior analysis of complex systems. Finally, the validity of the theoretical results has been verified by simulation examples.

The free-flying space manipulators present challenges in controlling the motions of both the spacecraft bus and the manipulator, because of the highly-coupling system dynamics and the unknown space environment disturbances. Although the sliding mode controllers are robust to the unknown disturbances and system uncertainties, the chattering effect could affect the pointing accuracy and the lifetime of the actuators. This paper first introduces the dynamics of a CuBot, which is a 3-rigid-link manipulator based on the CubeSat platform. To maintain the robustness while decreasing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. To maintain the robustness while reducing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. The switching gain is updated to estimate the lumped upper bound of the system uncertainties and the unknown disturbances, and then a new fuzzy logic adaptive law is applied on the switching gain to decrease the chattering effects. On top of that, the fuzzy logic rules are tuned by an innovative modified reinforcement learning mechanism to achieve the better tracking performance. The uniformly ultimately bounded tracking errors are guaranteed by the proposed control scheme, and the effectiveness is validated by the simulation results.

This paper presents a new adaptive small chattering sliding mode control (SCSMC) scheme that uses reinforcement learning (RL) and time-delay estimation (TDE) for the motion control of free-floating space robotic manipulators (FSRM) subject to model uncertainty and external disturbance. The proposed sliding mode control scheme can achieve small chattering effects and improve the tracking accuracy by using a new adaptive law for the switching gain and a RL-based robust term to handle the control inputs. In SCSMC, the complicated multiple-input-multiple-output (MIMO) uncertain system of FSRM is transformed into multiple single-input-single-output (SISO) known subsystems with bounded estimation errors by the TDE technique and state feedback compensation. Subsequently, once the sliding variable is inside the designed manifold, the derivative of the switching gain for each subsystem becomes a negative hyperbolic tangent function of the associated sliding variable, which offers the ability to reduce chattering by decreasing the switching gain. Moreover, the RL based robust term for each subsystem is designed to avoid the loss of tracking accuracy caused by the aforementioned switching gain drop. The tracking errors are proven to be uniformly-ultimately-bounded (UUB) with an arbitrarily small bound by using the Lyapunov theory. The effectiveness of the proposed control scheme is verified by numerical simulations.

Fuel cell based combined heat and power systems (FC-CHP) are a promising technology which can provide efficiently both electrical power and heat to residential and industrial consumers. However, FC-CHP system are typically complex in nature where much of the complexity arises from the necessary subsystems to operate the FC itself. This paper proposes a cost effective experimental emulator that acts like a real FC-CHP system by generating its key output characteristics while avoiding the complex component design of the real system. It achieves this by using two separate electrical circuits – One known as the Heat Emulator (HE) to emulate the waste heat characteristics and another, known as the Electric Power Emulator (EPE) to emulate the electrical power generation. Both circuits involve a controllable voltage source and a resistive load. A digital controller is then pre-programmed with an accurate FC model and its role is to control the source voltage and/or load resistance in the HE and EPE circuits such that these two circuits generate accurately the FC stack’s output characteristics. The HE circuit and a liquid cooling system is specifically implemented and water temperature control is used to study this system’s thermal efficiency.

The thermoelectric (TE) device enables a conversion interface between the heat transfer and the electricity domain. Specifically, it can operate bi-directionally – Heat can be converted to electricity via the thermoelectric generator (TEG) effect and vice versa via the thermoelectric cooling (TEC) effect. In most state of the art research, the TE device is operated either in the TEG mode or TEC mode but very seldom in both modes for a single control objective. This paper proposes a thermal management system for a fuel cell who exploits the bi-directional characteristics of the TE device to achieve both temperature control and the possibility for energy harvesting when active control is not required. The studied scenarios involve a time-based simulation involving heat generation levels that are typical of a 500 W rated operating proton exchange membrane fuel cell (PEMFC). The overall dynamic system is simulated using Simscape library components in Simulink and the controller itself is implemented using MATLAB s-functions. An experiment involving electric heaters to emulate the fuel cell’s body heat is also conducted to verify the proposed combined TEG-TEC control approach.

As a clean power system with a narrow temperature range of typically 60–95 °C, the low temperature (LT) proton exchange membrane fuel cell (PEMFC) requires an effective thermal management system to enhance its efficiency and durability. This paper focuses on a genetic algorithm based optimization of the thermoelectric generator (TEG) as applied to the PEMFC system. The genetic algorithm approach is advantageous over similar previous research in that it enables multi-objective optimization where the various TEG module parameters can be configured towards critical objectives such as maximum output power, minimal mass and maintaining the PEMFC within its operating temperature range. A second case study is also studied where the combined efficiency of the PEMFC and TEG is selected as an objective in replacement of the maximum TEG output power. Optimization results suggest that, in both cases, there is a trade-off situation between maximum output TEG power or maximum system efficiency with respect to system mass. It is also shown that the most important benefit of increasing the cooling convection coefficient is that it increases the system’s specific power where the heat sink areas can be smaller to achieve the same cooling rate.

The thermoelectric generator (TEG) is a clean and noiseless renewable electrical power source that requires no moving parts. In the meantime, the hybrid photovoltaic cell and thermoelectric generator (PV/TEG) system is also popularly considered in research because of its potential improved power conversion efficiency over its monolithic counterparts. This paper continues the work on several previous publications from the authors where the focus here is to perform maximum power point tracking (MPPT) on the hybrid PV/TEG system. It reuses the Lock-On Mechanism (LOM) MPPT algorithm which was previously used by the authors in two separate publications on the solar panel and TEG alone. In comparison to conventional fixed step based MPPT algorithms, the LOM algorithm improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle whenever the MPP is located. In doing so, the steady state oscillations become negligibly small thus be considered eliminated and a smooth steady state MPP response is achieved. The simulation and experiment in this paper are conducted using a double SEPIC converter where each input source is treated independently with the proposed algorithm. Results prove that the proposed algorithm is fast and stable in comparison to the conventional fixed step hill climbing algorithm.

The thermoelectric generator (TEG) is a clean and noiseless renewable electrical power source that requires no moving parts. Unfortunately, the practicality of TEGs is currently limited by its typical low conversion efficiencies. Subsequently, researchers have taken many approaches to improve the efficiency of the TEG. One of such approaches is the utilization of maximum power point tracking (MPPT) techniques. MPPT techniques are popularly used in literature for maximizing the power that is extracted from solar panels. Such techniques can be reused for the TEG scenario because TEGs also have I-V and P-V characteristics that follow the same principles as that of solar panels. This paper presents a “Lock-On Mechanism” MPPT algorithm and applies it specifically to the TEG application. In comparison to conventional fixed step based MPPT algorithms, the proposed algorithm improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle whenever the MPP is located. In doing so, the steady state oscillations become negligibly small thus be consideredeliminated and a smooth steady state MPP response is achieved. Simulation and experimental results prove that the proposed algorithm is fast and stable in comparison to the conventional fixed step hill climbing algorithm.

Maximum power point tracking (MPPT) techniques are popularly used for maximizing the output of solar panels by continuously tracking the maximum power point (MPP) of their P-V curves, which depend both on the panel temperature and the input insolation. Various MPPT algorithms have been studied in literature, including perturb and observe (P&O), hill climbing, incremental conductance, fuzzy logic control and neural networks. This paper presents an algorithm which improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle. The principle of the proposed algorithm is to detect the oscillation by checking the sign (ie. direction) of the duty cycle perturbation between the current and previous time steps. If there is a difference in the signs then it is clear an oscillation is present and the DC-DC converter duty cycle perturbation is subsequently scaled down by a constant factor. By repeating this process, the steady state oscillations become negligibly small which subsequently allows for a smooth steady state MPP response. To verify the proposed MPPT algorithm, a simulation involving irradiances levels that are typically encountered in outer space is conducted. Simulation and experimental results prove that the proposed algorithm is fast and stable in comparison to not only the conventional fixed step counterparts, but also to previous variable step size algorithms.

In this paper, the seepage finite element method (FEM) is used to simulate the transient seepage of Beijiang Dike, and antiseepage solutions are designed and discussed. By comparing the measured data of a piezometer with the steady-state calculation model, the calculated results are compatible very well with the measured data. Aiming to improve the ability to respond in extreme weather conditions, we calculate the transient seepage field after the water level suddenly rises in a short time and then select the relief well as the antiseepage measure and optimize it. The results show that when the water level is 15.78 m, the slope reaches 0.5, and the embankment is damaged. With the increase of penetration depth, the effect of drainage and decompression in the depth of 3/5 and 4/5 is relatively small due to geological strips. Due to different geological conditions, the same relief wells are placed in different positions with a wide gap in effect, the antiseepage effect is the best when the horizontal distance is 95 m, and the effect is the best when the depth is 16.5 m. The research results can be used to guide the seepage prevention and control design of Beijiang Dike.

In this paper, a bi-level Delta-Sigma modulator-based MEMS gyroscope design is presented based on a Model Predictive Control (MPC) approach. The MPC is popular because of its capability of handling hard constraints. In this work, we propose to combine the 1-bit nature of the bi-level Delta-Sigma modulator output with the MPC to develop a 1-bit processing-based MPC (OBMPC). This paper will focus on the affine relationship between the 1-bit feedback and the in-loop MPC controller, as this can potentially remove the multipliers from the controller. In doing so, the computational requirement of the MPC control is significantly alleviated, which makes the 1-bit MEMS Gyroscope feasible for implementation. In addition, a stable constrained MPC is designed, so that the input will not overload the quantizer while maintaining a higher Signal-to-Noise Ratio (SNR).

Although interfacial atmospheric water generation is a new concept that can generate freshwater from renewable energy, its water generation rate is too low for widespread use. This paper proposes to integrate the fuel cell to a similar device but instead uses the electrochemically generated waste heat to drive the regeneration process of the liquid sorbent material. Furthermore, the electrochemically generated water is used to increase the relative humidity of the incoming air. Thus, by solely relying on the fuel cell waste products, water recovery rates that are theoretically higher than direct atmospheric water generation are achieved. A steady-state physics model based on the difference in water partial pressure to achieve water absorption and desorption is used to analyze the liquid sorbent device’s performance. Furthermore, the effect of various design parameters such as the salt mass fraction, the fuel cell operating power, the ambient relative humidity, etc. have been studied. Results demonstrate that up to 1.8 kg/h and 0.82 kg/(m2 h) of liquid water can be obtained by fuel cells with an operating temperature range that is consistent with the high-temperature proton exchange membrane fuel cell. This implementation would allow an FC waste heat utilization ratio of up to 0.8.

The thermoelectric generator (TEG) has been widely considered as an electrical power source in many ground applications because of its clean and noiseless characteristics. Moreover, the hybrid photovoltaic cell and TEG (PV/TEG) system has also received wide attention due to its improved power conversion efficiency over its monolithic counterparts. This paper presents a study of the dynamics and the operation of the hybrid PV/TEG system in an outer space environment where a unified thermodynamic model of this system is presented. Moreover, the multi-objective NSGA-II genetic algorithm is utilized to optimize the design of the TEG both in terms of optimal output power and in terms of mass. Specifically, the design of the single stage and the two stage variant of the aforementioned TEG are considered. Simulation results indicate that the optimized PV/TEG system does indeed achieve better efficiencies than that of the monolithic counterparts. Furthermore, it is shown that the single stage TEG is more beneficial than the two stage TEG in terms of achieving optimal performance.

Despite the success of atmospheric water generators for providing drinking water to remote regions, this technology has a high specific energy consumption. This paper proposes to reuse the electrochemical water of the fuel cell for the vapor compression cycle based atmospheric water generator (VCC-AWG); After passing through an ambient heat exchanger to remove the electrochemical waste heat, the fuel cell flue gas that enters the VCC-AWG is at a higher relative humidity than natural atmospheric air, thus the freshwater yield per energy input can be significantly increased. Hence, the FC-VCC-AWG hybrid system is proposed to be a power and freshwater supply of a grid-independent home. The fuel cell model, the vapor compression cycle’s thermodynamic model, and humid air physics are coupled to analyze the overall system in terms of the fuel cell’s working condition, incoming airflow rate, compressor power consumption, and the ambient relative humidity. When RH = 0.75, adding a 2 kW fuel cell generated up to 3 kg/hr of freshwater, which is 50% higher than excluding the FC. The specific energy consumption can be 200 Wh/kg, so the VCC-AWG can be integrated with small sacrifices to the FC power output.

Medium temperature solar thermal systems have a great prospect to be an efficient energy source for practical industrial applications. Although the evacuated flat solar collector is a potential non-concentrating collector for this application, current designs have not fully demonstrated its superiority. In this paper, a medium-scale (50.96 m2) solar thermal system based on an efficiently optimized evacuated flat plate solar collector structure is designed. A systematic four months long real-time experiment under the natural environment is conducted for medium solar thermal applications in a region with four distinct seasons. An annual performance analysis is then conducted in four different locations through a validated numerical model. Experimental results demonstrate that, when the inlet temperature is 123.0 °C, the ambient temperature is 35.7 °C and the solar irradiation is 835.2 W/m2, the thermal efficiency and exergy efficiency can reach 59.67% and 14.35%, respectively. The efficiently optimized evacuated flat plate solar collector can also achieve a stable annual average thermal efficiency at the four studied locations with values reaching up to 50%. Therefore, the superiority of this efficiently optimized evacuated flat plate solar collector design over previous ones is demonstrated.

The parabolic trough system is one of the main technological routes to achieve high-temperature solar thermal conversion. The parabolic trough system is a mature technology and can be easily coupled with distributed systems. However, the parabolic trough receiver, which is a key component of the parabolic trough system, suffer from enormous radiation heat loss at high temperature. An analytical model based on spectral-spatial coupling distributed parameters is developed. Analytical results reveal that >40% surface area of the absorber is negative thermal-flux region and exposes the widely long-term thermal performance weakness in circumferentially uniform receiver design. A local optimal cutoff wavelength is reported. Results show that the exists asymmetrical design of the receiver can reduce radiation heat loss by approximately 41.0% and improve photothermal efficiency by 10.2–42.0% as solar irradiation varies from 1000 W/m2 to 200 W/m2 at 600 °C. The asymmetric design may be a promising choice for optimization of the receiver due to the strong heterogeneity of the solar flux distribution at high temperature. The discovery of negative thermal-flux region and local optimal cutoff wavelength also leads to the optimization of other concentrated solar technologies for improving photothermal performance.

Previously, the combined thermoelectric generator and cooler (TEG-TEC) control technique was proposed for thermal management of devices, where the TEG mode is used for energy harvesting and the TEC mode is used for active temperature control. This research significantly improves the TEG-TEC control technique by including the components that ensure the TEG output power can truly be returned to the original power source. Specifically, two cascaded boost converters are adopted in the TEG power circuit where the former is used to achieve maximum power point tracking, and the latter provides an additional constant voltage gain to improve the circuit’s compatibility. Both a Simscape based simulation model and the modified experimental platform involving a lithium ion battery is used to demonstrate the improved implementation. Moreover, for the sake of demonstration, two control algorithms, namely the basic nested IF loop and a fuzzy logic controller, are adopted and their performances are compared. Finally, a steady state analysis of the Simscape model involving a parametric sweep of the input waste heat shows that the TEG mode can only be engaged for a certain range.

Optimization of an air conditioning system is critical in terms of the transient and steady state behavior of the air distribution along the room and the temperature of the equipment themselves. In this paper, three computational techniques, namely, the standard k-ε, RNG k-ε, and the k-ω model, are used to numerically simulate and determine the air distribution in an air-conditioned room. The simulation results for all three methods are verified via a comparison with an experiment involving a room that contains a computer server which generates up to 6 kW of heat. In doing so and by additionally performing an error analysis, it is determined that the k-ω model produces the most accurate results. The results also indicated that the direction of air supply from the air conditioners has a strong impact on the velocity field and temperature distribution along the room and on the computer server. Hence, many candidate directions of air supply options were selected for study and by conducting a performance evaluation in terms of air temperature around the server, the optimal solution was obtained.

Although integrating the thermoelectric device (TED) to fuel cells (FC) is a promising way to improve the overall system’s output efficiency, its application to the micro-combined heat and power (μCHP) application requires an effective energy management strategy. Therefore, this paper aims to develop a real time energy management strategy (EMS) that intelligently allows the FC and TED to cooperatively minimize primary energy consumption and startup time while properly balancing energy in the energy storage components. This EMS is unique in that it includes TED’s mode of operation and FC and TED’s operating powers as controller parameters for a multi-input multi-output (MIMO) controller. As such, it regulates FC and water tank temperatures and the electric battery’s state of charge. The proposed overall system is tested under 3 dynamic simulations that include startup from ambient and satisfying the energy demands during a winter and summer day. Results demonstrate that adding the TED has reduced startup times by up to 4.45 and 1.77 times for the 1 kW FC stack and 50 kg water tank respectively. Primary energy consumption efficiencies also improved by up to 3.4% in winter and 5.6% in summer when the TED is included into the system.

This paper reports the near space ballooning experiment carried out at Australian outback town West Wyalong (33°51′S, 147°24′E) on 19 July 2015. Several dedicated electronic detectors including digital temperature and acceleration (vibration) sensors and an energy compensated PIN-diode gamma ray dosimeter were installed in a thermally insulated Styrofoam payload box. A 9V Lithium-Polymer battery powered all the devices. The payload box was attached to a helium-filled latex weather balloon and set afloat. The balloon reached a peak burst altitude of 30km and then soft-landed aided by a self-deploying parachute 66.2km away form the launch site. The payload box was retrieved and data collected from the electronic sensors analysed. The integrated cosmic ray induced photon ambient dose equivalent recorded by the PIN diode detector was evaluated to be 0.36±0.05μSv. Furthermore, a high-altitude extended version of commercially available aviation dosimetry package EPCARD.Net (European Program package for the Calculation of Aviation Route Doses) was used to calculate the ambient dose equivalents during the balloon flight. The radiation environment originated from the secondary cosmic ray shower is composed of neutrons, protons, electrons, muons, pions and photons. The photon ambient dose equivalent estimated by the EPCARD.Net code found to be 0.47±0.09μSv. The important aspects of balloon based near-space radiation dosimetry are highlighted in this paper.