Parvathy Rajendran

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.

Modeling and Simulation of Solar Irradiance and Daylight Duration for a High-Power-Output Solar Module System

Solar energy is the largest available renewable energy for enhancing the endurance of a solar-powered unmanned aerial vehicle (UAV). However, harnessing solar energy is a great challenge because the power output efficiency of solar module systems is only 15% to 30%. A solar-powered UAV has the potential to outperform a battery-powered UAV, particularly in tasks involving a pseudo satellite that requires long operating hours. Atmospheric conditions and geographical location are the main causes of the poor performance of solar modules. Despite the improvements in solar cell efficiency over the years, solar module systems can still barely convert half of the sun’s power into electricity. This limitation hinders the use of current solar module systems for harvesting solar energy. Recent studies have focused not only on the type of solar cells but also on the positioning system. However, understanding and research on the solar irradiance intensity, as well as on the effect of daylight duration on the power output, remain lacking. A comprehensive model was developed to address this gap and investigate how the movement of the sun movement affects the performance of solar module systems. This simulation model found that daylight duration is more important than available solar irradiance. Higher solar irradiance and daylight duration corresponds to a higher power output of the solar module system. Daylight duration also depends on latitude where higher latitudes lead to longer daylight duration. On the other hand, longitudinal coordinates and elevation have minor effects on the estimation of daylight duration. Therefore, the northern hemisphere has more advantages than southern hemisphere during summer and vice versa.

The Development of a Small Solar Powered Electric Unmanned Aerial Vehicle Systems

Unmanned Aerial Vehicle (UAV) has an enormous role to both military and civilian missions. However, a short range endurance of current UAV system affects the life expediency, data monitoring, and output performance of a mission. This is due to having UAVs that are dependent on batteries. The weight of the battery and low temperature environment has undoubtedly been the main cause for the poor UAV performance. In spite of its prolific improvement in UAV system, the endurance permissible is between 45 minutes to 4 hours. Therefore, this situation makes battery no longer attractive to be widely used for UAV. Lately attention has been focused on the use of solar cell in UAV in replacement to battery as its power system. Nevertheless, current solar cells characteristic and efficiency is insufficient to sustain a long endurance flight. This is due to failure to identify an appropriate selection of material and parts in designing the UAVs solar augmented power module system. Therefore, comprehensive work on the solar power system and its integration is essential for an excellent UAV performance. Thus, a research work has been done to studies on the design of a solar and battery power system for an electric UAV. Subsequently, a small solar powered electric UAV has been developed. As a result, the UAVs specification, layout and systems description are presented extensively in this paper. This UAV has enabled an understanding how the solar augmented system has enhanced the endurance performance the electric UAV to almost 24 hours. Moreover, this UAV has 5 successfully flight up till date with useful data that predicted this UAV aerodynamic characteristic.

Power Management Strategy by Enhancing the Mission Profile Configuration of Solar-Powered Aircraft

Solar energy offers solar-powered unmanned aerial vehicle (UAV) the possibility of unlimited endurance. Some researchers have developed techniques to achieve perpetual flight by maximizing the power from the sun and by flying in accordance with its azimuth angles. However, flying in a path that follows the sun consumes more energy to sustain level flight. This study optimizes the overall power ratio by adopting the mission profile configuration of optimal solar energy exploitation. Extensive simulation is conducted to optimize and restructure the mission profile phases of UAV and to determine the optimal phase definition of the start, ascent, and descent periods, thereby maximizing the energy from the sun. In addition, a vertical cylindrical flight trajectory instead of maximizing the solar inclination angle has been adopted. This approach improves the net power ratio by 30.84% compared with other techniques. As a result, the battery weight may be massively reduced by 75.23%. In conclusion, the proposed mission profile configuration with the optimal power ratio of the trajectory of the path planning effectively prolongs UAV operation.

Regression Model to Predict Global Solar Irradiance in Malaysia

A novel regression model is developed to estimate the monthly global solar irradiance in Malaysia. The model is developed based on different available meteorological parameters, including temperature, cloud cover, rain precipitate, relative humidity, wind speed, pressure, and gust speed, by implementing regression analysis. This paper reports on the details of the analysis of the effect of each prediction parameter to identify the parameters that are relevant to estimating global solar irradiance. In addition, the proposed model is compared in terms of the root mean square error (RMSE), mean bias error (MBE), and the coefficient of determination () with other models available from literature studies. Seven models based on single parameters (PM1 to PM7) and five multiple-parameter models (PM7 to PM12) are proposed. The new models perform well, with RMSE ranging from 0.429% to 1.774%, ranging from 0.942 to 0.992, and MBE ranging from −0.1571% to 0.6025%. In general, cloud cover significantly affects the estimation of global solar irradiance. However, cloud cover in Malaysia lacks sufficient influence when included into multiple-parameter models although it performs fairly well in single-parameter prediction models.

Evaluation of satellite and meteorology data to estimate solar irradiance over five cities in Malaysia

In this paper, meteorology and satellite data are evaluated to estimate global and direct solar irradiance over Malaysia. The meteorology data consist of direct solar irradiance were for 2013 and the satellite data were global solar irradiance from year 2000 till 2004. The estimated global solar irradiance were then compared with observe satellite data and their performance were judge by using statistical indicators, including root mean squared error and mean percentage error. The 5 cities studied in Malaysia includes Kota Kinabalu (KK), Kuching (KC), Ipoh (IP), Alor Setar (AS) and Kuantan (KU). The yearly average of hourly solar irradiance for all 5 cities throughout a year lies between 193 W/m2 and 208 W/m2. The highest solar irradiance has been estimated at 216 W/m2 in the month of March due to the dry season, and the minimum solar irradiance is predicted in the month of December is 164 W/m2 that coincides with the rainy season in Malaysia. Results show that the proposed global and direct solar irradiance models present good regression coefficient (R2) value of 0.9661 and 0.9549 respectively. The average diffuse solar irradiance cast over these cities were 3.0% (correction factor) of global solar irradiance. Since Malaysian government are focusing on renewable and clean energy, these models and analyses will benefit the government and education department for further development in solar technologies.

Investigation on selection schemes and population sizes for genetic algorithm in unmanned aerial vehicle path planning

Genetic algorithm has been widely used in numerous fields. Recently, researchers have developed significant interest in applying GA in unmanned aerial vehicle path planning. However, experiments should be conducted to determine selection schemes and population sizes. This process is time consuming and inconvenient for users. Thus, a study is conducted on the performance of GA at various selection schemes and population sizes. Results show that large population sizes do not contribute in improving the performance of GA. Tournament selection shows the highest performance in terms of path cost, whereas the weakest performance is in terms of computational cost. Truncation selection shows the optimum performance among the selection schemes.

Development of design methodology for a small solar-powered unmanned aerial vehicle

Existing mathematical design models for small solar-powered electric unmanned aerial vehicles (UAVs) only focus on mass, performance, and aerodynamic analyses. Presently, UAV designs have low endurance. The current study aims to improve the shortcomings of existing UAV design models. Three new design aspects (i.e., electric propulsion, sensitivity, and trend analysis), three improved design properties (i.e., mass, aerodynamics, and mission profile), and a design feature (i.e., solar irradiance) are incorporated to enhance the existing small solar UAV design model. A design validation experiment established that the use of the proposed mathematical design model may at least improve power consumption-to-take-off mass ratio by 25% than that of previously designed UAVs. UAVs powered by solar (solar and battery) and nonsolar (battery-only) energy were also compared, showing that nonsolar UAVs can generally carry more payloads at a particular time and place than solar UAVs with sufficient endurance requirement. The investigation also identified that the payload results in the highest effect on the maximum take-off weight, followed by the battery, structure, and propulsion weight with the three new design aspects (i.e., electric propulsion, sensitivity, and trend analysis) for sizing consideration to optimize UAV designs.

Single Cell Li-Ion Polymer Battery Charge and Discharge Characterizations for Application on Solar-Powered Unmanned Aerial Vehicle

Solar-powered UAV is an alternative way to achieve high endurance and long range UAV flight. However, solar irradiance is not always available during the flight. Thus, secondary power source which is electrical batteries will improve the performance of solar-powered UAV when solar irradiance is not available. Therefore, bench test for LiPo battery is conducted in this paper for the design of solar-powered UAV power system. The impact of operating temperature at various charging and discharging rate on the duration to full charge and discharge and capacity level of a single LiPo battery were assessed. The solar module installed in solar-powered UAV developed by Aircraft Design Group, Cranfield University has to be designed to charge the battery pack at a nominal or maximum rate of 0.129 C and 0.155 C correspondingly. The solar module requires roughly 5.73 hours on nominal charging rate on 30 °C operating temperature to fully charge capacity level instead of 5.54 hours theoretical predicted. The battery pack will then discharge at cruise flight roughly about 0.071 C to a maximum of 1.685 C if required. If the battery pack is not charged, during cruise flight the battery capacity will deplete completely at about 6.51 hours for the same operating temperature, in contrast to the 6.48 hours based on the theoretical prediction. In addition, the usage of LiPo batteries for operation at high altitudes and/or extreme temperatures without an additional heating or cooling system for these battery packs is not favorable. Thus, it is best to charge at low charging rate and high operating temperature to store and utilize the most capacity from this battery.

Proportional-derivative linear quadratic regulator controller design for improved longitudinal motion control of unmanned aerial vehicles

This study investigates the longitudinal motion control of unmanned aerial vehicles through a simulation in MATLAB. The linear model of an unmanned aerial vehicle is applied to controllers to explicate the longitudinal motion of the unmanned aerial vehicle. The ideal performance for an unmanned aerial vehicle is to achieve the desired response instantly with 100% precision. However, currently available controllers need further improvements. Thus, a proportional-derivative linear quadratic regulator controller is developed and compared with a proportional-integral-derivative controller, a linear quadratic regulator controller, and a proportional linear quadratic regulator controller. The proportional-derivative linear quadratic regulator controller enhances the response of the system by reducing settling time by more than 95% compared with other available controllers. Additionally, the proportional-derivative linear quadratic regulator improves the root mean square error by almost 50% compared with the proportional linear quadratic regulator controller and improves rise time by almost 96% with reasonable overshoot.