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Article
Publication date: 14 July 2021

Maryam Bahrami, Mehdi Khashei and Atefeh Amindoust

The purpose of this paper, because of the complexity of demand time series and the need to construct a more accurate hybrid model that can model all relationships in data, is to…

Abstract

Purpose

The purpose of this paper, because of the complexity of demand time series and the need to construct a more accurate hybrid model that can model all relationships in data, is to propose a parallel-series hybridization of seasonal neural networks and statistical models for demand time series forecasting.

Design/methodology/approach

The main idea of proposed model is centered around combining parallel and series hybrid methodologies to use the benefit of unique advantages of both hybrid strategies as well as intelligent and classic seasonal time series models simultaneously for achieving results that are more accurate for the first time. In the proposed model, in contrast of traditional parallel and series hybrid strategies, it can be generally shown that the performance of the proposed model will not be worse than components.

Findings

Empirical results of forecasting two well-known seasonal time series data sets, including the total production value of the Taiwan machinery industry and the sales volume of soft drinks, indicate that the proposed model can effectively improve the forecasting accuracy achieved by either of their components used in isolation. In addition, the proposed model can achieve more accurate results than parallel and series hybrid model with same components. Therefore, the proposed model can be used as an appropriate alternative model for seasonal time series forecasting, especially when higher forecasting accuracy is needed.

Originality/value

To the best of the authors’ knowledge, the proposed model, for first time and in contrast of traditional parallel and series hybrid strategies, is developed.

Article
Publication date: 13 May 2021

Aiping Jiang, Zhenni Huang, Jiahui Xu and Xuemin Xu

The purpose of this paper is to propose a condition-based opportunistic maintenance policy considering economic dependence for a seriesparallel hybrid system with a K-out-of-N

Abstract

Purpose

The purpose of this paper is to propose a condition-based opportunistic maintenance policy considering economic dependence for a seriesparallel hybrid system with a K-out-of-N redundant structure, where a single component in series is denoted as subsystem1, and K-out-of-N redundant structure is denoted as subsystem2.

Design/methodology/approach

Based on the theory of Residual Useful Life (RUL), inspection points are determined, and then different maintenance actions are adopted in the purpose of minimizing the cost rate. Both perfect and imperfect maintenance actions are carried out for subsystem1. More significantly, regarding economic dependence, condition-based opportunistic maintenance is designed for the seriesparallel hybrid system: preemptive maintenance for subsystem1, and both preemptive and postponed maintenance for subsystem2.

Findings

The sensitivity analysis indicates that the proposed policy outperforms two classical maintenance policies, incurring the lowest total cost rate under the context of both heterogeneous and quasi-homogeneous K-out-of-N subsystems.

Practical implications

This model can be applied in seriesparallel systems with redundant structures that are widely used in power transmission systems in electric power plants, manufacturing systems in textile factories and sewerage systems. Considering inconvenience and high cost incurred in the inspection of hybrid systems, this model helps production managers better maintain these systems.

Originality/value

In maintenance literature, much attention has been received in repairing strategies on hybrid systems with economic dependence considering preemptive maintenance. Limited work has considered postponed maintenance. However, this paper uses both condition-based preemptive and postponed maintenance on the issue of economic dependence bringing opportunities for grouping maintenance activities for a seriesparallel hybrid system.

Details

Journal of Quality in Maintenance Engineering, vol. 28 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 8 August 2022

Lionel Dongmo Fouellefack, Lelanie Smith and Michael Kruger

A hybrid-electric unmanned aerial vehicle (HE-UAV) model has been developed to address the problem of low endurance of a small electric UAV. Electric-powered UAVs are not capable…

Abstract

Purpose

A hybrid-electric unmanned aerial vehicle (HE-UAV) model has been developed to address the problem of low endurance of a small electric UAV. Electric-powered UAVs are not capable of achieving a high range and endurance due to the low energy density of its batteries. Alternatively, conventional UAVs (cUAVs) using fuel with an internal combustion engine (ICE) produces more noise and thermal signatures which is undesirable, especially if the air vehicle is required to patrol at low altitudes and remain undetected by ground patrols. This paper aims to investigate the impact of implementing hybrid propulsion technology to improve on the endurance of the UAV (based on a 13.6 kg UAV).

Design/methodology/approach

A HE-UAV model is developed to analyze the fuel consumption of the UAV for given mission profiles which were then compared to a cUAV. Although, this UAV size was used as reference case study, it can potentially be used to analyze the fuel consumption of any fixed wing UAV of similar take-off weight. The model was developed in a Matlab-Simulink environment using Simulink built-in functionalities, including all the subsystem of the hybrid powertrain. That is, the ICE, electric motor, battery, DC-DC converter, fuel system and propeller system as well as the aerodynamic system of the UAV. In addition, a ruled-based supervisory controlled strategy was implemented to characterize the split between the two propulsive components (ICE and electric motor) during the UAV mission. Finally, an electrification scheme was implemented to account for the hybridization of the UAV during certain stages of flight. The electrification scheme was then varied by changing the time duration of the UAV during certain stages of flight.

Findings

Based on simulation, it was observed a HE-UAV could achieve a fuel saving of 33% compared to the cUAV. A validation study showed a predicted improved fuel consumption of 9.5% for the Aerosonde UAV.

Originality/value

The novelty of this work comes with the implementation of a rule-based supervisory controller to characterize the split between the two propulsive components during the UAV mission. Also, the model was created by considering steady flight during cruise, but not during the climb and descend segment of the mission.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 3
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 15 July 2022

Mehrnaz Ahmadi and Mehdi Khashei

The purpose of this paper is to propose a new linear-nonlinear data preprocessing-based hybrid model to achieve a more accurate result at a lower cost for wind power forecasting…

Abstract

Purpose

The purpose of this paper is to propose a new linear-nonlinear data preprocessing-based hybrid model to achieve a more accurate result at a lower cost for wind power forecasting. For this purpose, a decomposed based series-parallel hybrid model (PKF-ARIMA-FMLP) is proposed which can model linear/nonlinear and certain/uncertain patterns in underlying data simultaneously.

Design/methodology/approach

To design the proposed model at first, underlying data are divided into two categories of linear and nonlinear patterns by the proposed Kalman filter (PKF) technique. Then, the linear patterns are modeled by the linear-fuzzy nonlinear series (LLFN) hybrid models to detect linearity/nonlinearity and certainty/uncertainty in underlying data simultaneously. This step is also repeated for nonlinear decomposed patterns. Therefore, the nonlinear patterns are modeled by the linear-fuzzy nonlinear series (NLFN) hybrid models. Finally, the weight of each component (e.g. KF, LLFN and NLFN) is calculated by the least square algorithm, and then the results are combined in a parallel structure. Then the linear and nonlinear patterns are modeled with the lowest cost and the highest accuracy.

Findings

The effectiveness and predictive capability of the proposed model are examined and compared with its components, based models, single models, series component combination based hybrid models, parallel component combination based hybrid models and decomposed-based single model. Numerical results show that the proposed linear-nonlinear data preprocessing-based hybrid models have been able to improve the performance of single, hybrid and single decomposed based prediction methods by approximately 66.29%, 52.10% and 38.13% for predicting wind power time series in the test data, respectively.

Originality/value

The combination of single linear and nonlinear models has expanded due to the theory of the existence of linear and nonlinear patterns simultaneously in real-world data. The main idea of the linear and nonlinear hybridization method is to combine the benefits of these models to identify the linear and nonlinear patterns in the data in series, parallel or series-parallel based models by reducing the limitations of the single model that leads to higher accuracy, more comprehensiveness and less risky predictions. Although the literature shows that the combination of linear and nonlinear models can improve the prediction results by detecting most of the linear and nonlinear patterns in underlying data, the investigation of linear and nonlinear patterns before entering linear and nonlinear models can improve the performance, which in no paper this separation of patterns into two classes of linear and nonlinear is considered. So by this new data preprocessing based method, the modeling error can be reduced and higher accuracy can be achieved at a lower cost.

Article
Publication date: 3 August 2022

Dominik Quillet, Vincent Boulanger, David Rancourt, Richard Freer and Pierre Bertrand

Parallel hybrid electric (HE) propulsion retrofit is a promising alternative to reduce fuel burn of aircraft operating on short regional flights. However, if the batteries are…

Abstract

Purpose

Parallel hybrid electric (HE) propulsion retrofit is a promising alternative to reduce fuel burn of aircraft operating on short regional flights. However, if the batteries are depleted at the end of the mission, the hybrid powertrain designs with downsized gas turbines (GTs) and additional electric motors might not meet the one-engine inoperative (OEI) missed approach climb performance required by the certification. Alternatively, hybrid designs using the original full-size GT can perform one engine climb without electric assistance. This paper aims to evaluate the impact of overshoot climb requirements on powertrain design and performance comparing the two design approaches.

Design/methodology/approach

An aircraft-level parametric mission analysis model is used to evaluate aircraft performance combined with an optimization framework including multiple constraints. An indirect approach using metamodels is used to optimize powertrain sizing and operation strategy.

Findings

Considering OEI climb requirements, no benefits were found using a design with downsized GTs. Equivalent fuel burns were found for hybrid designs that keep the original size GTs, but do not require electric energy for the OEI overshoot at the end of the mission. Then, it is recommended to size the GT to maintain the emergency climb capabilities with no electric assistance to ensure power availability regardless of remaining battery energy.

Originality/value

This work introduces a new perspective on parallel HE sizing with consideration for the dependency of power capability at aircraft level on the electric energy availability in case of critical mission scenarios such as overshoot climb at the end of the mission.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 2
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 14 April 2020

Axel Yezeguelian and Askin T. Isikveren

When comparing and contrasting different types of fixed-wing military aircraft on the basis of an energetic efficiency figure-of-merit, unmanned aerial vehicles (UAVs) dedicated…

Abstract

Purpose

When comparing and contrasting different types of fixed-wing military aircraft on the basis of an energetic efficiency figure-of-merit, unmanned aerial vehicles (UAVs) dedicated to tactical medium-altitude long-endurance (MALE) operations appear to have significant potential when hybrid-electric propulsion and power systems (HEPPS) are implemented. Beginning with a baseline Eulair drone, this paper aims to examine the feasibility of retro-fitting with an Autarkic-Parallel-HEPPS architecture to enhance performance of the original single diesel engine.

Design/methodology/approach

In view of the low gravimetric specific energy performance attributes of batteries in the foreseeable future, the best approach was found to be one in which the Parallel-HEPPS architecture has the thermal engine augmented by an organic rankine cycle (ORC). For this study, with the outer mould lines fixed, the goal was to increase endurance without increasing the Eulair drone maximum take-off weight beyond an upper limit of +10%. The intent was to also retain take-off distance and climb performance or, where possible, improve upon these aspects. Therefore, as the focus of the work was on power scheduling, two primary control variables were identified as degree-of-hybridisation for useful power and cut-off altitude during the en route climb phase. Quasi-static methods were used for technical sub-space modelling, and these modules were linked into a constrained optimisation algorithm.

Findings

Results showed that an Autarkic-Parallel-HEPPS architecture comprising an ORC thermal energy recovery apparatus and high-end year-2020 battery, the endurance of the considered aircraft could be increased by 11%, i.e. a total of around 28 h, including de-icing system, in-flight recharge and emergency aircraft recovery capabilities. The same aircraft with the de-icing functionality removed resulted in a 20% increase in maximum endurance to 30 h.

Practical implications

Although the adoption of Series/Parallel-HEPPS only solutions do tend to generate questionable improvements in UAV operational performance, combinations of HEPPS with energy recovery machines that use, for example, an ORC, were found to have merit. Furthermore, such architectural solutions could also offer opportunity to facilitate additional functions like de-icing and emergency aircraft recovery during engine failure, which is either not available for UAVs today or prove to be prohibitive in terms of operational performance attributes when implemented using a conventional PPS approach.

Originality/value

This technical paper highlights a new degree of freedom in terms of power scheduling during climbing transversal flight operations. A control parameter of cut-off altitude for all types of HEPPS-based aircraft should be introduced into the technical decision-making/optimisation/analysis scheme and is seen to be a fundamental aspect when conducting trade-studies with respect to degree-of-hybridisation for useful power.

Details

Aircraft Engineering and Aerospace Technology, vol. 92 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 1 February 1998

Manolis Papadrakakis, Nikolaos D. Lagaros, Georg Thierauf and Jianbo Cai

The objective of this paper is to investigate the efficiency of hybrid solution methods when incorporated into large‐scale optimization problems solved by evolution strategies

Abstract

The objective of this paper is to investigate the efficiency of hybrid solution methods when incorporated into large‐scale optimization problems solved by evolution strategies (ESs) and to demonstrate their influence on the overall performance of these optimization algorithms. ESs imitate biological evolution and combine the concept of artificial survival of the fittest with evolutionary operators to form a robust search mechanism. In this paper modified multi‐membered evolution strategies with discrete variables are adopted. Two solution methods are implemented based on the preconditioned conjugate gradient (PCG) algorithm. The first method is a PCG algorithm with a preconditioner resulted from a complete Cholesky factorization, and the second is a PCG algorithm in which a truncated Neumann series expansion is used as a preconditioner. The numerical tests presented demonstrate the computational advantages of the proposed methods, which become more pronounced in large‐scale optimization problems and in a parallel computing environment.

Details

Engineering Computations, vol. 15 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 1 January 2013

Omar Hegazy, Joeri Van Mierlo, Ricardo Barrero, Noshin Omar and Philippe Lataire

The purpose of this paper is to optimize the design and power management control fuel cell/supercapacitor and fuel cell/battery hybrid electric vehicles and to provide a…

Abstract

Purpose

The purpose of this paper is to optimize the design and power management control fuel cell/supercapacitor and fuel cell/battery hybrid electric vehicles and to provide a comparative study between the two configurations.

Design/methodology/approach

In hybrid electric vehicles (HEVs), the power flow control and the powertrain component sizing are strongly related and their design will significantly influence the vehicle performance, cost, efficiency and fuel economy. Hence, it is necessary to assess the power flow management strategy at the powertrain design stage in order to minimize component sizing, cost, and the vehicle fuel consumption for a given driving cycle. In this paper, the PSO algorithm is implemented to optimize the design and the power management control of fuel cell/supercapacitor (FC/SC) and fuel cell/battery (FC/B) HEVs for a given driving cycle. The powertrain and the proposed control strategy are designed and simulated by using MATLAB/Simulink. In addition, a comparative study of fuel cell/supercapacitor and fuel cell/battery HEVs is analyzed and investigated for adequately selecting of the appropriate HEV, which could be used in industrial applications.

Findings

The results have demonstrated that it is possible to significantly improve the hydrogen consumption in fuel cell hybrid electric vehicles (FCHEVs) by applying the PSO approach. Furthermore, by analyzing and comparing the results, the FC/SC HEV has slightly higher fuel economy than the FC/B HEV.

Originality/value

The addition of electrical energy storage such as supercapacitor or battery in fuel cell‐based vehicles has a great potential and a promising approach for future hybrid electric vehicles (HEV). This paper is mainly focused on the optimal design and power management control, which has significant influences on the vehicle performance. Therefore, this study presents a modified control strategy based on PSO algorithm (CSPSO) for optimizing the power sharing between sources and reducing the components sizing. Furthermore, an interleaved multiple‐input power converter (IMIPC) is proposed for fuel cell hybrid electric vehicle to reduce the input current/output voltage ripples and to reduce the size of the passive components with high efficiency compared to conventional boost converter. Meanwhile, the fuel economy is improved. Moreover, a comparative study of FC/SC and FC/B HEVs will be provided to investigate the benefits of hybridization with energy storage system (ESS).

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 32 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 18 December 2019

Teresa Donateo, Antonio Ficarella and Claudia Lucia De Pascalis

The purpose of this study is to investigate the optimization of design and energy management in a parallel hybrid-electric powertrain to replace the conventional engine of an…

Abstract

Purpose

The purpose of this study is to investigate the optimization of design and energy management in a parallel hybrid-electric powertrain to replace the conventional engine of an existing tactical unmanned aerial vehicle (UAV) equipped with a Wankel engine with a pre-defined flight mission. The proposed powertrain can work in four different operating modes: electric, thermal, power-assist and charging.

Design/methodology/approach

The power request at propeller axis of each flight segment is used as input for an in-house model that calculates the overall fuel consumption throughout the mission (Mfuel) and the maximum payload weight (Wpay) by means of an average-point analysis. These outputs depend on the energy management strategy that is expressed by the power-split ratio between engine and electric phase (Uphase) of each mission phase, according to which the components of the hybrid system are sized. The in-house model is integrated into an optimization framework to find the optimal set of Uphase and battery size that minimizes Mfuel and maximizes Wpay.

Findings

It was found a 3.24% saving of the fuel mass burned throughout the mission (or, alternative an improvement of endurance by 4.3%) with about the same maximum-payload mass (+0.2%) of the original configuration, or a smaller fuel saving with +11% more payload. The fuel saving of 3.24% corresponds to −3.25% in total emissions of CO2 and a 2.34% reduction of the cost-per-mission.

Practical implications

This study demonstrates that environmental advantages, even if limited, can be already obtained from optimal design and management of the hybrid power system with today technologies while waiting for further benefits from the introduction of advanced technologies for batteries and electric machines.

Originality/value

The main novelties are the design of the powertrain on the basis of the energy management and the application of scalability and hybridization to Wankel engines.

Details

Aircraft Engineering and Aerospace Technology, vol. 92 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 18 May 2021

Yanzhang Yao, Wei Wang, Yue Qiao, Zhihang He, Fusheng Liu, Xuelong Li, Xinxin Liu, Dehua Zou and Tong Zhang

The purpose of this paper is to describe the design and development of a novel series-parallel robot, which aims to climb on the transmission tower.

Abstract

Purpose

The purpose of this paper is to describe the design and development of a novel series-parallel robot, which aims to climb on the transmission tower.

Design methodology approach

This study introduces a hybrid robot, which consists of adsorption and two 3-degree of freedom (DOF) translation parallel legs connected by a body linkage. The DOF of the legs ensures that the robot can move on the climbing plane, also contribute to a compact design of the robot. An electromagnet is used to adsorb onto the transmission tower, simplifying the overall structure. Based on the robot design, this paper further defines its climbing gait and adopt the 6th B-spline curves for climbing trajectory planning under different working environments.

Findings

The developed prototype that implements the design of the robot, which was used in simulation and experiments, showing that the robot is capable of climbing in the test environments with the planned climbing gait.

Originality value

The hybrid robot is able to climb under varying degrees of inclinations and cross the obstacles, and the magnetic attraction can ensure stable climbing.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

1 – 10 of over 3000