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The purpose of this study is to perform the preliminary design, flight performance and exhaust emissions calculations of a piston engine powered unmanned aerial vehicle (UAV) during a flight cycle which consists of multiple flight altitudes and airspeeds.

A genuine computer model in Matlab/Simulink was developed to predict the size and weight of UAV and piston engine (using Avgas 100LL fuel) performance together with exhaust emissions in an iterative process.

The amount of emitted exhaust gases including carbon dioxide, carbon monoxide, hydrocarbons and nitrogen oxides were calculated in a typical UAV mission profile as a whole and also divided into mission flight segments.

Emissions were calculated based on fuel flow and engine speed inputs based on ground test data for emission indices. Test data for emission indices was very limited.

As UAV utilization has been increasing around the world, this study presents important and noticeable results on the emissions that need to be considered for environmental purposes.

In literature, emission prediction studies for UAVs are very rare. In fact, UAVs typically have quite different flight speeds and altitudes than regular manned aircraft and emissions change with speed and altitude. Additionally, unlike manned aircraft, UAVs can fly more than 24 h with different operation characteristics. The originality of this study presents the emission predictions of a piston engine UAV which flies with a significantly different mission profile than a manned aircraft.

This paper aims to present a genuine code developed for multi-objective optimization of selected parameters of a turboprop unmanned air vehicle (UAV) for minimum landing-takeoff (LTO) nitrogen oxide (NOx) emissions and minimum equivalent power specific fuel consumption (ESFC) at loiter (aerial reconnaissance phase of flight) by using a genetic algorithm.

The genuine code developed in this study first makes computations on preliminary sizing of a UAV and its turboprop engine by analytical method for a given mission profile. Then, to minimize NOx emissions or ESFC or both of them, single and multi-objective optimization was done for the selected engine design parameters.

In single objective optimization, NOx emissions were reduced by 49 per cent from baseline in given boundaries or constraints of compressor pressure ratio and compressor polytropic efficiency in the first case. In second case, ESFC was improved by 25 per cent from baseline. In multi-objective optimization case, where previous two objectives were considered together, NOx emissions and ESFC decreased by 26.6 and 9.5 per cent from baseline, respectively.

Variation and trend in the NOx emission index and ESFC were investigated with respect to two engine design parameters, namely, compressor pressure ratio and compressor polytropic efficiency. Engine designers may take into account the findings of this study to reach a viable solution for the bargain between NOx emission and ESFC.

UAVs have different flight mission profiles or characteristics compared to manned aircraft. Therefore, they are designed in a different philosophy. As a number of UAV flights increase in time, fuel burn and LTO NOx emissions worth investigating due to operating costs and environmental reasons. The study includes both sizing and multi-objective optimization of an UAV and its turboprop engine in coupled form; compared to manned aircraft.

This paper aims to present experimental experience of heavy fuelling of a spark ignition crankcase scavenged two-stroke cycle unmanned aerial vehicle (UAV) engine, particularly focusing on the effects of compression ratio variation, and to cross-correlate with the results of fluid dynamic modelling of the engine and fuels used.

One-dimensional modelling of the engine has been conducted using WAVE software supported by experimental dynamometer testing of a spark ignition UAV engine to construct a validated computational model using gasoline and kerosene JET A-1 fuels.

The investigation into the effects of compression ratio variation via fluid dynamic simulation and experimental testing has allowed an assessment of the approach for improving heavy fuel operation of UAV engines using auxiliary transfer port fuel injection. The power level achieved with reduced compression ratio heavy fuel operation is equal to 15.35 kW at 6,500 revolutions per minute compared to 16.27 kW from the standard gasoline engine or a reduction of 5.7%.

The studied engine is specifically designed for UAV applications. The validation of the computational models to explore the effects of compression ratio and heavy fuel injection on the solution and cost is supported by experimental tests.

The application of auxiliary port fuel injection of heavy fuel and associated compression ratio optimisation offers an alternative approach to achieve the safety and logistical challenges of the single fuel policy for UAVs. The application of WAVE to simulate crankcase scavenged two-stroke cycle engines has been applied in very few cases. This study shows further exploratory work in that context.

The purpose of this paper is to present results of practical experience of cold starting a gasoline engine on low volatility fuel suitable for unmanned aerial vehicle (UAV) deployment.

Experimental research and development is carried out via dynamometer testing of systems capable of achieving cold start of a spark ignition UAV engine on kerosene JET A-1 fuel.

Repeatable cold starts have been satisfactorily achieved at ambient temperatures of 5°C. The approximate threshold for warm engine restart has also been established.

For safety and supply logistical reasons, the elimination of the use of gasoline fuel offers major advantages not only for UAVs but also for other internal combustion engine-powered equipment to be operated in military theatres of operation. For gasoline crankcase-scavenged two-stroke cycle engines, this presents development challenges in terms of modification of the lubrication strategy, achieving acceptable performance characteristics and the ability to successfully secure repeatable engine cold start.

The majority of UAVs still operate on gasoline-based fuels. Successful modification to allow low volatility fuel operation would address single fuel policy objectives.

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.

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.

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.

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.

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.

The purpose of this paper is to present a multi‐objective and multi‐point optimization method to support the preliminary design of an unmixed turbofan mounted on a sample UAV/UCAV aircraft.

An in‐house multi‐objective evolutionary algorithm, a flight simulator and a validated engine simulator are implemented and joined together using object‐oriented programming.

Optimal values are found of the pressure ratio and corrected mass flow of both the engine fan and compressor as they operate in on/off design conditions (multipoint approach), as well as the engine by‐pass ratio, that contextually minimize time and engine fuel consumption required to cover a fixed trajectory (mission profile). Furthermore, the optimal distribution of the thermodynamic quantities along the trajectory is determined.

The research deals with a preliminary design of an engine, therefore no detailed engine geometry can be found.

The paper shows how a multiobjective and multipoint approach to the design of an engine can affect the choice of the engine architecture. In particular, major practical implications regard how the mission profile can affect the choice of the design point: in fact, there is no longer a definitive design point but the design of a UAV/UCAV should be addressed as a function of the mission profile.

The paper presents a multiobjective and multipoint approach to engine optimization as a function of the mission profile.

Determining the performance parameters of the propulsion systems of the aircraft, which is the key product of the aviation industry, plays a critical role in reducing adverse environmental impacts. Therefore, the purpose of this paper is to present a temperature performance template for turbojet engines at the design stage using a neural network model that defines the relationship between the performance parameters obtained from ground tests of a turbojet engine used in unmanned aerial vehicles (UAV).

The main parameters of the flow passing through the engine of the UAV propulsion system, where ground tests were performed, were obtained through the data acquisition system and injected into a neural network model created. Fifteen sensors were mounted on the engine – six temperature sensors, six pressure sensors, two flow meters and one load cell were connected to the data acquisition system to make sense of this physical environment. Subsequently, the artificial neural network (ANN) model as a complement to the approach was used. Thus, the predicted model relationship with the experimental data was created.

Fuel flow and thrust parameters were estimated using these components as inputs in the feed-forward neural network. In the network experiments to estimate fuel flow parameter, r-square and mean absolute error were calculated as 0.994 and 0.02, respectively. Similarly, for thrust parameter, these metrics were calculated as 0.994 and 1.42, respectively. In addition, the correlation between fuel flow, thrust parameters and each input parameters was examined. According to this, air compressor inlet (AC_inlet,temp) and outlet (AC_outlet,temp) temperatures and combustion chamber (CC_inlet,temp, CC_outlet,temp) temperature parameters were determined to affect the output the most. The proposed ANN model is applicable to any turbojet engines to model its behavior.

Today, deep neural networks are the driving force of artificial intelligence studies. In this study, the behavior of a UAV is modeled with neural networks. Neural networks are used here as a regressor. A neural network model has been developed that predicts fuel flow and thrust parameters using the real parameters of a UAV turbojet engine. As a result, satisfactory findings were obtained. In this regard, fuel flow and thrust values of any turbojet engine can be estimated using the neural network hyperparameters proposed in this study. Python codes of the study can be accessed from https://github.com/tekinonlayn/turbojet.

The originality of the study is that it reports the relationships between turbojet engine performance parameters obtained from ground tests using the neural network application with open source Python code. Thus, small-scale unmanned aerial propulsion system provides designers with a template showing the relationship between engine performance parameters.

The lack of airworthiness and certification criteria for the employment of UAV vehicles in the civilian field has caused an uncontrolled proliferation of projects and the construction of a number of UAV prototypes which differ in dimension, weight, flight characteristics and payload carriage. This paper is aimed at identifying the most important project criteria which may concur to unifying the main UAV characteristics. In particular, the minimum take‐off weight is investigated which is able to guarantee the adherence to the levels of safety required by the airworthiness design requirement (ADR) currently being developed. To this end, the characteristics of mission and the safety requirements currently available in the ADR have been examined. and the safety characteristics and reliability of the UAVs used in the military field have also been considered. After which, an assessment is made of the on‐board system and the relative redundancies necessary for adjusting such characteristics to meet the ADR. Taking into account the weight of systems, payload and other UAV components (engine, structure, etc.), a reasonable estimation of the take‐off weight as well as the geometrical dimensions of a certifiable UAV are obtained.

This paper seeks to evaluate the potential of heat exchanged aeroengines for future Unmanned Aerial Vehicle (UAV), helicopter, and aircraft propulsion, with emphasis placed on reduced emissions, lower fuel burn, and less noise.

Aeroengine performance analyses were carried out covering a wide range of parameters for more complex thermodynamic cycles. This led to the identification of major component features and the establishing of preconceptual aeroengine layout concepts for various types of recuperated and ICR variants.

Novel aeroengine architectures were identified for heat exchanged turboshaft, turboprop, and turbofan variants covering a wide range of applications. While conceptual in nature, the results of the analyses and design studies generally concluded that heat exchanged engines represent a viable solution to meet demanding defence and commercial aeropropulsion needs in the 2015‐2020 timeframe, but they would require extensive development.

As highlighted in Parts I and II, early development work was focused on the use of recuperation, but this is only practical with compressor pressure ratios up to about 10. For today's aeroengines with pressure ratios up to about 50, improvement in SFC can only be realised by incorporating intercooling and recuperation. The new aeroengine concepts presented are clearly in an embryonic stage, but these should enable gas turbine and heat exchanger specialists to advance the technology by conducting more in‐depth analytical and design studies to establish higher efficiency and “greener” gas turbine aviation propulsion systems.

It is recognised that meeting future environmental and economic requirements will have a profound effect on aeroengine design and operation, and near‐term efforts will be focused on improving conventional simple‐cycle engines. This paper has addressed the longer‐term potential of heat exchanged aeroengines and has discussed novel design concepts. A deployment strategy, aimed at gaining confidence with emphasis placed on assuring engine reliability, has been suggested, with the initial development and flight worthiness test of a small recuperated turboprop engine for UAVs, followed by a larger recuperated turboshaft engine for a military helicopter, and then advancement to a larger and far more complex ICR turbofan engine.

This paper aims to present experimental results of gasoline-fuelled engine operation of a crankcase-scavenged two-stroke cycle engine used for unmanned air vehicle (UAV)/unmanned air system application and to cross correlate with computational fluid dynamic modelling results.

Computational modelling of the engine system was conducted using the WAVE software supported by the experimental research and development via dynamometer testing of a spark ignition UAV engine to construct a validated computational model exploring a range of fuel delivery options.

Experimental test data and computational simulation have allowed an assessment of the potential advantages of applying direct in-cylinder fuel injection.

The ability to increase system efficiency offers significant advantages in terms of maximising limited resources and extending mission duration capabilities. The computational simulation and validation via experimental test experience provides a means of assessment of possibilities that are costly to explore experimentally and offers added confidence to be able to investigate possibilities for the development of similar future engine designs.

The software code used has not been applied to such crankcase-scavenged two-stroke cycle engines and provides a valuable facility for further simulation of the twin cylinder horizontally opposed design to offer further system optimisation and exploration of future possibilities.