CERES :: Browsing by Author "Economou, John T."

Browsing by Author "Economou, John T."

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Open Access
Design of a distributed hybrid electric propulsion system for a light aircraft based on genetic algorithm
(AIAA, 2019-08-16) Economou, John T.; Tsourdos, Antonios; Wang, Siqi
Hybrid aircraft is a new attempt for next-generation aircraft, they are environmentally friendly and highly efficient. This paper proposes a new type of hybrid electric propulsion system for light aircraft, which integrated distributed propulsion concept and more electric aircraft concept together to improve aircraft performance. Based on the mission requirements and unique system configuration, all components, including engine, generator and motors are intelligently selected. The sizing problem can be divided into two parts. The power source part applied a non-dominated sorting genetic algorithm to choose components and simultaneously minimized total weight and fuel consumption. The rest of the system used a conventional genetic algorithm, which minimized weight and guaranteed that all selected motors can output enough power. In the end, by applying a simple deterministic energy management strategy, the new system achieved a 12% fuel consumption reduction.
Open Access
Evaluation of off-road uninhabited ground vehicle mobility using discrete element method and scalability investigation
(2022-09) Nuwal, A; Economou, John T.; Kumar, A
Full-scale military vehicles are teaming up with uninhabited ground vehicles (UGVs) to improve the success rate of tactical operations on off-road terrains. UGV can perform initial mobility testing on soft soils during missions to evaluate the performance (e.g., go/ no-go) of full-scale military vehicles. Therefore, the concept of scale model testing is proposed. The scale model testing can be divided into two parts, i.e. the scalability of soil and the scalability of the tyre-soil interaction. The scalability of soil is defined as a relationship between the mechanical properties of an in-situ terrain (heterogeneous) system and a laboratory (homogeneous) soil system while accounting for the differences in sand, silt and clay particle shapes and size distributions. Physical properties such as moisture content, bulk density, compaction, and interparticle forces are kept the same for laboratory and in-situ terrain conditions. The 2NS and fine-grained sands were modelled using the discrete element method with Edinburgh elastic-plastic adhesion contact model. It was found that the scalability depends on the testing conditions and the soil’s nature. The heterogeneity of soil affects the cohesive and adhesive forces present in the soil system. The pressure-sinkage and shear stress vs shear displacement relationships are found scalable. The cone index vs depth relation is not scalable. The scale model testing can be divided into two parts, i.e. the scalability of soil and the scalability of the tyre-soil interaction. The scalability of soil is defined as a relationship between the mechanical properties of an in-situ terrain (heterogeneous) system and a laboratory (homogeneous) soil system while accounting for the differences in sand, silt and clay particle shapes and size distributions. Physical properties such as moisture content, bulk density, compaction, and interparticle forces are kept the same for laboratory and in-situ terrain conditions. The 2NS and fine-grained sands were modelled using the discrete element method with Edinburgh elastic-plastic adhesion contact model. It was found that the scalability depends on the testing conditions and the soil’s nature. The heterogeneity of soil affects the cohesive and adhesive forces present in the soil system. The pressure-sinkage and shear stress vs shear displacement relationships are found scalable. The cone index vs depth relation is not scalable.Further, the scalability of tyre-soil interaction is established using the dimensional analysis method to establish similarity in the full-scale and scaled systems. The developed non dimensional parameters are kept the same in both systems. In this research, the lightweight Armoured Personnel Carriers such as the FED Alpha and Land Rover are considered as the full-scale systems (upper boundary) and UGVs for example, the Husky or Warthog as a scaled system (lower boundary). Consequently, the tyre-soil interaction behaviour is similar in this specific tyre size and loading range. The full-scale tyre modelled is FED Alpha tyre 335/65R22.5 and is scaled down by size to scales 0.7, 0.5 and 0.25. Six different terrain simulation models of both sands were prepared with cone indexes ranging from 14.79 kPa to 149 kPa. It was found that the drawbar pull and tractive efficiency vs slip relations are scalable. The mean error in drawbar pull prediction w.r.t. NATO experiments is 12% and 9% for 2NS and fine-grained sand, respectively. The drawbar pull varies from square to cubic power w.r.t. the scale of the system. The gross traction varies with square power w.r.t. the scale of the system. The tractive efficiency is constant w.r.t. the scale of the system. It is concluded that a 0.5 scale system can predict the full-scale system’s mobility performance on sands. This key finding can be used to design and develop cost-effective and lighter UGVs to support full-scale military vehicles on the battlefield. The limitation of the DEM technique is that it is computationally expensive as the number of particles increases.
Open Access
A graph-theory-based C-space path planner for mobile robotic manipulators in close-proximity environments
(2016-08-10) Galvão Wall, David; Economou, John T.
In this thesis a novel guidance method for a 3-degree-of-freedom robotic manipulator arm in 3 dimensions for Improvised Explosive Device (IED) disposal has been developed. The work carried out in this thesis combines existing methods to develop a technique that delivers advantages taken from several other guidance techniques. These features are necessary for the IED disposal application. The work carried out in this thesis includes kinematic and dynamic modelling of robotic manipulators, T-space to C-space conversion, and path generation using Graph Theory to produce a guidance technique which can plan a safe path through a complex unknown environment. The method improves upon advantages given by other techniques in that it produces a suitable path in 3-dimensions in close-proximity environments in real time with no a priori knowledge of the environment, a necessary precursor to the application of this technique to IED disposal missions. To solve the problem of path planning, the thesis derives the kinematics and dynamics of a robotic arm in order to convert the Euclidean coordinates of measured environment data into C-space. Each dimension in C-space is one control input of the arm. The Euclidean start and end locations of the manipulator end effector are translated into C-space. A three-dimensional path is generated between them using Dijkstra’s Algorithm. The technique allows for a single path to be generated to guide the entire arm through the environment, rather than multiple paths to guide each component through the environment. The robotic arm parameters are modelled as a quasi-linear parameter varying system. As such it requires gain scheduling control, thus allowing compensation of the non-linearities in the system. A Genetic Algorithm is applied to tune a set of PID controllers for the dynamic model of the manipulator arm so that the generated path can then be followed using a conventional path-following algorithm. The technique proposed in this thesis is validated using numerical simulations in order to determine its advantages and limitations.
Open Access
Hypersurface normalised gain-scheduled controller for a non-linear 6-DOF fast jet
(Elsevier, 2020-07-25) Hamilton, Jordan; Galvão Wall, David; Saddington, A. J.; Economou, John T.
This paper describes a novel approach for improving the dynamic response of a bank-to-turn autopilot for a non-linear six degree-of-freedom (6-DoF) aircraft model. The autopilot consists of a series of gain-scheduled (GS) proportional, integral and derivative (PID) controllers that govern the aircraft's angular velocities for roll, pitch and yaw. The controller gains have been optimised for localised trim points and applied continuously to the controllers using linear interpolation to form a hypersurface. Our novel solution has been achieved by implementing a set of scheduled gains for near-zero reference signals and integrating this with a set of gains that are normalised to the reference signal. The proposed approach has been compared to conventional gain scheduling techniques using a series of step input simulated manoeuvres, applied individually to the roll and pitch controllers. The results show improved rise and fall times, steady state errors, as well as reduced controller effort
Open Access
H∞/LQR optimal control for a supersonic air-breathing missile of asymmetric configuration
(Elsevier, 2019-11-25) Vincent, Raymond Vin; Economou, John T.; Galvão Wall, David; Cleminson, John
Robust control is challenging to achieve for air-breathing missiles operating in a high Mach number regime, such as at high supersonic speeds (M > 3). The challenge arises because of strong couplings, significant non-linearities and large uncertainties in the aerodynamics and propulsion system. The feasibility of achieving robust control in such applications is strongly linked to the development of an appropriate control design structure. The purpose of this paper is to illustrate that in order to stabilise a highly unstable airframe and achieve the required performance, a hybrid of two control schemes may be used to achieve best results. A state feedback linear quadratic regulator is used to stabilise the plant and a forward path H∞ optimal controller is used to achieve the required performance and robustness. We also highlight the complementary attributes of the two control schemes that together can generate a more robust controller; LQR is used since it can achieve good gain and phase margins, whereas, the H∞ control method is better equipped to deal with uncertainties.
Open Access
Indirect engine sizing via distributed hybrid-electric unmanned aerial vehicle state-of-charge-based parametrisation criteria
(SAGE Publications, 2019-04-28) Wang, Siqi; Economou, John T.; Tsourdos, Antonios
This paper presents a design process for the challenging problem of sizing the engine pack for a Distributed Series Hybrid Electric Propulsion System (DSHEPS) of Unmanned Aircraft Vehicle (UAV). Sizing the propulsion system for hybrid electric UAVs is a demanding problem because of the two different categories of propulsion, (the engine and the motor), and the electrical system characteristics. Furthermore, what adds to the difficulty is that the Internal Combustion Engine (ICE) does not directly drive the propellers, but it is connected to an electrical generator and therefore provides electrical power to the Electric Motors (EM) and propellers. Hence there is a clear distinction from the traditional engine solutions which are mechanically coupled to the propeller. This paper addresses this specific distinction and proposes an indirect solution based on properties on the electrical part of the system. In particular, a novel parametric characterisation engine sizing approach is presented using the battery pack State-of-Charge (SOC) during a realistic UAV flight scenario. Five candidate engine options were considered with different starting conditions for the electrical system. The results show that by using the SOC properties it is possible to select an appropriate size of engine pack while carrying a suitable electrical propulsion pack. However, the solutions are not unique and are appropriate for given design criteria clearly indicated in the paper.
Open Access
Indirect tuning of a complementary orientation filter using velocity data and a genetic algorithm
(Taylor and Francis, 2024-04-23) Maton, Dariusz; Economou, John T.; Galvão Wall, David; Khan, Irfan; Cooper, Robert; Ward, David; Trythall, Simon
In this paper, the accuracy of inertial sensor orientation relative to the level frame is improved through optimal tuning of a complementary filter by a genetic algorithm. While constant filter gains have been used elsewhere, these may introduce errors under dynamic motions when gyroscopes should be trusted more than accelerometers. Optimal gains are prescribed by a Mamdani fuzzy rule base whose membership functions are found using a genetic algorithm and experimental data. Furthermore, model fitness is not based directly on orientation but the error between estimated and ground truth velocities. This paper has three interrelated novel elements. The main novelty is the indirect tuning method, which is simple, low-cost and requires a single camera and inertial sensor. The method is shown to increase tracking accuracy compared with popular baseline filters. Secondary novel elements are the bespoke genetic algorithm and the time agnostic velocity error metric. The contributions from this work can help improve the localization accuracy of assets and human personnel. This research has a direct impact in command and control by improving situational awareness and the ability to direct assets to safe locations using safer routes. This results in increasing safety in applications such as firefighting and battlespace.
Open Access
Intelligent based terrain preview controller for a 3-axle vehicle
(AVEC 16, 2016-09-16) Economou, John T.; Purdy, David J.; Galvão Wall, David; Diskett, D.; Simner, D.
The paper presents a six-wheel half longitudinal model and the design of a dual level control architecture. The first (top) level is designed using a Sugeno fuzzy inference feedforward architecture with and without preview. The second level of controllers are locally managing each wheel for each axle. As the vehicle is moving forward the front wheels and suspension units will have less time to respond when compared to the middle and rear units, hence a preview sensor is used to compensate. The paper shows that the local active suspensions together with the Sugeno Fuzzy, (locally optimised using subtractive clustering), Feedforward control strategy is more effective and this architecture has resulted in reducing the sprung mass vertical acceleration and pitch accelerations.
Open Access
An intelligent power management system for unmanned earial vehicle propulsion applications
(2013-10-08) Karunarathne, L; Economou, John T.
Electric powered Unmanned Aerial Vehicles (UAVs) have emerged as a promi- nent aviation concept due to the advantageous such as stealth operation and zero emission. In addition, fuel cell powered electric UAVs are more attrac- tive as a result of the long endurance capability of the propulsion system. This dissertation investigates novel power management architecture for fuel cell and battery powered unmanned aerial vehicle propulsion application. The research work focused on the development of a power management system to control the hybrid electric propulsion system whilst optimizing the fuel cell air supplying system performances. The multiple power sources hybridization is a control challenge associated with the power management decisions and their implementation in the power electronic interface. In most applications, the propulsion power distribu- tion is controlled by using the regulated power converting devices such as unidirectional and bidirectional converters. The amount of power shared with the each power source is depended on the power and energy capacities of the device. In this research, a power management system is developed for polymer exchange membrane fuel cell and Lithium-Ion battery based hybrid electric propulsion system for an UAV propulsion application. Ini- tially, the UAV propulsion power requirements during the take-off, climb, endurance, cruising and maximum velocity are determined. A power man- agement algorithm is developed based on the UAV propulsion power re- quirement and the battery power capacity. Three power states are intro- duced in the power management system called Start-up power state, High power state and Charging power state. The each power state consists of the power management sequences to distribute the load power between the battery and the fuel cell system. A power electronic interface is developed Electric powered Unmanned Aerial Vehicles (UAVs) have emerged as a promi- nent aviation concept due to the advantageous such as stealth operation and zero emission. In addition, fuel cell powered electric UAVs are more attrac- tive as a result of the long endurance capability of the propulsion system. This dissertation investigates novel power management architecture for fuel cell and battery powered unmanned aerial vehicle propulsion application. The research work focused on the development of a power management system to control the hybrid electric propulsion system whilst optimizing the fuel cell air supplying system performances. The multiple power sources hybridization is a control challenge associated with the power management decisions and their implementation in the power electronic interface. In most applications, the propulsion power distribu- tion is controlled by using the regulated power converting devices such as unidirectional and bidirectional converters. The amount of power shared with the each power source is depended on the power and energy capacities of the device. In this research, a power management system is developed for polymer exchange membrane fuel cell and Lithium-Ion battery based hybrid electric propulsion system for an UAV propulsion application. Ini- tially, the UAV propulsion power requirements during the take-off, climb, endurance, cruising and maximum velocity are determined. A power man- agement algorithm is developed based on the UAV propulsion power re- quirement and the battery power capacity. Three power states are intro- duced in the power management system called Start-up power state, High power state and Charging power state. The each power state consists of the power management sequences to distribute the load power between the battery and the fuel cell system. A power electronic interface is developed with a unidirectional converter and a bidirectional converter to integrate the fuel cell system and the battery into the propulsion motor drive. The main objective of the power management system is to obtain the controlled fuel cell current profile as a performance variable. The relationship between the fuel cell current and the fuel cell air supplying system compressor power is investigated and a referenced model is developed to obtain the optimum compressor power as a function of the fuel cell current. An adaptive controller is introduced to optimize the fuel cell air supplying system performances based on the referenced model. The adaptive neuro-fuzzy inference system based controller dynamically adapts the actual compressor operating power into the optimum value defined in the reference model. The online learning and training capabilities of the adaptive controller identify the nonlinear variations of the fuel cell current and generate a control signal for the compressor motor voltage to optimize the fuel cell air supplying system performances. The hybrid electric power system and the power management system were developed in real time environment and practical tests were conducted to validate the simulation results.
Open Access
Intelligent-based hybrid-electric propulsion system for aero vehicle
(Cranfield University, 2020-03) Wang, Siqi; Tsourdos, Antonios; Economou, John T.
To address the sustainability challenges for air transport, electrified aviation delivers promising benefits to the whole air transportation system. Focusing on reducing environmental impact and raising competitiveness, this thesis presents a research regarding the Distributed Series Hybrid-electric Propulsion System for aero vehicles, which involves study fields of system configuration design, component sizing and energy management strategies. Based on the state-of-art of hybrid-electric aircraft and hybrid-electric propulsion systems, the study firstly improved the conventional series hybrid configuration by adopting distributed propulsion technology and more electric aircraft concept. These improvements can compensate for the drawbacks caused by the conventional series hybrid layout, so that the new designed propulsion system has the potential to reduce system weight and increase fuel economy. After that, a comprehensive sizing method was particularly designed for the proposed system. The engine, as the primary power source, was firstly selected via the battery parametrisation criteria. Then, other components were selected according to a proposed sizing flowchart by using the genetic algorithm. System performance can also be demonstrated during the sizing process. Finally, three different control methods had been applied to manage energy flows. The first supervisory controller is a deterministic rule-based controller, which was designed based on human experiences and can reduce 12% fuel consumption. The second is a battery-friendly fuzzy controller. It was particularly designed to improve the battery operating environment and can simultaneously achieve a 5% improvement on fuel economy compared to the rule-based. The third controller applied model predictive control algorithm, which can further improve the fuel efficiency by 4% and reveal the relationship between the fuel consumption and emissions.
Open Access
Kinetic energy recovery and power management for hybrid electric vehicles
(2011-09-08) Suntharalingam, P.; Economou, John T.
The major contribution of the work presented in this thesis is a thorough investigation of the constraints on regenerative braking and kinetic energy recovery enhancement for electric/hybrid electric vehicles during braking. Regenerative braking systems provide an opportunity to recycle the braking energy, which is otherwise dissipated as heat in the brake pads. However, braking energy harnessing is a relatively new concept in the automotive sector which still requires further research and development. Due to the operating constraints of the drivetrain architecture and the varying nature of the braking conditions, it is unlikely that all the stored kinetic energy of the vehicle can be recovered during braking.The research work in this thesis addresses the effect of braking conditions on kinetic energy recovery enhancement of the vehicle. The challenge in kinetic energy recovery enhancement lies in braking conditions, power/torque handling ability of the electric propulsion system, managing the dual braking systems, employed energy conversion techniques, and energy storage capacity. In this work a novel braking strategy is introduced to increase the involvement of the regenerative braking system, so as to increase the kinetic energy recovery while achieving the braking performance requirements. Initially mathematical modelling and simulation based analysis are presented to demonstrate the effects of braking power variation with respect to braking requirements. A novel braking strategy is proposed to increase the kinetic energy recovery during heavy braking events. The effectiveness of this braking strategy is analyzed using a simulation model developed in matlab- simulink environment. Anexperimental rig is developed to test various braking scenarios and their effects on kinetic energy recovery. A variety of braking scenarios are tested and results are presented with the analysis. At the end, suggestions are made to further continue this research in the future.
Open Access
Kinetic energy storage using a dual braking system for unmanned parallel hybrid electric vehicle
(Sage / IMECHE, 2016-11-06) Suntharalingam, P.; Economou, John T.; Knowles, Kevin
In this paper a novel regenerative dual braking strategy is proposed for utility/goods delivery unmanned vehicles in public roads, which improves the regenerative energy capturing ability and consequently improves the fuel use of parallel hybrid power train configurations for land unmanned vehicles where the priority is not comfort but extending the range. Furthermore, the analysis takes into account the power handling ability of the electric motor and the power converters. In previous research a plethora of regenerative braking strategies is shown, for this paper the key contribution is that the vehicle electric regeneration is related to a fixed braking distance in relation to the energy storage capabilities specifically for unmanned utility type land vehicles where passenger comfort is not a concern but pedestrian safety is of critical importance. Furthermore, the vehicle’s power converter capabilities facilitate the process of extending the braking time via introducing a variable deceleration profile. The proposed approach has therefore resulted in a regenerative algorithm which improves the vehicle’s energy storage capability without considering comfort since this analysis is applicable to unmanned vehicles. The algorithm considers the distance as the key parameter, which is associated to safety, therefore it allows the braking time period to be extended thus favouring the electric motor generation process while sustaining safety. This method allows the vehicle to brake for longer periods rather than short bursts hence resulting in a more effective regeneration with reduced use of the dual (i.e. caliper/stepper motor brake system). The regeneration method and analysis is addressed in the following paper sections. The simulation results show that the proposed regenerative braking strategy has improved significantly the energy recapturing ability of the hybrid power train configuration. The paper is also supported with experimental data that verify the theoretical development and the simulation results. The two strategies developed and implemented are Constant Braking Torque (CBT) and Constant Braking Power (CBP). Both methods were limited to a fixed safety-based distance. Overall the results demonstrate that the CBT method results in better energy-based savings.
Open Access
Multi-mode electric actuator dynamic modelling for missile fin control
(MDPI, 2017-06-14) Gurav, Bhimashankar; Economou, John T.; Saddington, A. J.; Knowles, Kevin
Linear first/second order fin direct current (DC) actuator model approximations for missile applications are currently limited to angular position and angular velocity state variables. Furthermore, existing literature with detailed DC motor models is decoupled from the application of interest: tail controller missile lateral acceleration (LATAX) performance. This paper aims to integrate a generic DC fin actuator model with dual-mode feedforward and feedback control for tail-controlled missiles in conjunction with the autopilot system design. Moreover, the characteristics of the actuator torque information in relation to the aerodynamic fin loading for given missile trim velocities are also provided. The novelty of this paper is the integration of the missile LATAX autopilot states and actuator states including the motor torque, position and angular velocity. The advantage of such an approach is the parametric analysis and suitability of the fin actuator in relation to the missile lateral acceleration dynamic behaviour
Open Access
A novel dual-spin actuation mechanism for small calibre, spin stabilised, guided projectiles
(2021) Norris, James J.; Hameed, Amer; Economou, John T.
Small calibre projectiles are spin-stabilised to increase ballistic stability, often at high frequencies. Due to hardware limitations, conventional actuators and meth ods are unable to provide satisfactory control at such high frequencies. With the reduced volume for control hardware and increased financial cost, incorporating traditional guid ance methods into small-calibre projectiles is inherently difficult. This work presents a novel method of projectile control which addresses these issues and conducts a systems level analysis of the underlying actuation mechanism. The design is shown to be a viable alternative to traditional control methods, Firstly, a 7 Degree-of-Freedom (DoF) dynamic model is created for dual-spin pro jectiles, including aerodynamic coefficients. The stability of dual-spin projectiles, gov erned by the gyroscopic and dynamic stability factors is given, discussed and unified across available literature. The model is implemented in a Matlab/Simulink simulation environ ment, which is in turn validated against a range of academic literature and experimental test data. The novel design and fundamental operating principle are presented. The actuation mechanism (AM) is then mathematically formulated from both a velocity change (∆V ) and a lateral acceleration (a˜) perspective. A set of axioms are declared and verified using the 7-DoF model, showing that the inherently discrete system behaviour can be controlled continuously via these control variables, ∆V or a˜. Control state switching is simplified to be instantaneous, then expanded to be generically characterised by an arbitrarily complex mathematical function. A detailed investigation, parametric analysis and sensitivity study is undertaken to understand the system behaviour. A Monte Carlo procedure is described, which is used to compare the correction cap abilities of different guidance laws (GLs). A bespoke Zero-Effort-Miss (ZEM) based GLis synthesised from the mathematical formulation of the AM, with innately more know ledge of the system behaviour, which allows superior error correction. This bespoke GL is discussed in detail, a parametric study is undertaken, and both the GL parameters and PID controller gains are optimised using a genetic algorithm. Artificial Intelligence (AI) Reinforcement learning methods are used to emulate a GL, as well as controlling the AM and operating as a GL, simultaneously. The novel GLs are compared against a traditional proportional navigation GL in a nominal system and all GLs were able to control the AMs, reducing the miss distance to a satisfactory margin. The ZEM-based GL provided superior correction to the AI GL, which in turn provided superior correction over proportional navigation. Example CAD models are shown, and the stability analysis is conducted on the geometry. The CAD model is then used in CFD simulations to determine aerodynamic coefficients for use in the 7-DoF dynamic model. The novel control method was able to reduce the 95% dispersion diameter of a traditional ballistic 7.62mm projectile from 70mm to 33mm. Statistical data analysis showed there was no significant correlation or bias present in either the nominal or 7-DoF dispersion patterns. This project is co-sponsored by BAE Systems and ESPRC (ref. 1700064). The con tents of this thesis are covered by patent applications GB2011850.1, GB 2106035.5 and EP 20275128.5. Two papers are currently published (DOI: 10.1016/j.dt.2019.06.003, the second DOI is pending) and one is undergoing peer review..
Open Access
A novel framework for identifying the threshold of trust-worthiness of Artificial Intelligence
(Cranfield University, 2021-10-12) Forsyth, Tim; Kumar, Ajay; Economou, John T.
Open Access
A novel power management and control design framework for resilient operation of microgrids
(2017-10) Al Khafaji, Mohammed H.; Luk, Patrick Chi-Kwong; Economou, John T.
This thesis concerns the investigation of the integration of the microgrid, a form of future electric grids, with renewable energy sources, and electric vehicles. It presents an innovative modular tri-level hierarchical management and control design framework for the future grid as a radical departure from the ‘centralised’ paradigm in conventional systems, by capturing and exploiting the unique characteristics of a host of new actors in the energy arena - renewable energy sources, storage systems and electric vehicles. The formulation of the tri-level hierarchical management and control design framework involves a new perspective on the problem description of the power management of EVs within a microgrid, with the consideration of, among others, the bi-directional energy flow between storage and renewable sources. The chronological structure of the tri-level hierarchical management operation facilitates a modular power management and control framework from three levels: Microgrid Operator (MGO), Charging Station Operator (CSO), and Electric Vehicle Operator (EVO). At the top level is the MGO that handles long-term decisions of balancing the power flow between the Distributed Generators (DGs) and the electrical demand for a restructure realistic microgrid model. Optimal scheduling operation of the DGs and EVs is used within the MGO to minimise the total combined operating and emission costs of a hybrid microgrid including the unit commitment strategy. The results have convincingly revealed that discharging EVs could reduce the total cost of the microgrid operation. At the middle level is the CSO that manages medium-term decisions of centralising the operation of aggregated EVs connected to the bus-bar of the microgrid. An energy management concept of charging or discharging the power of EVs in different situations includes the impacts of frequency and voltage deviation on the system, which is developed upon the MGO model above. Comprehensive case studies show that the EVs can act as a regulator of the microgrid, and can control their participating role by discharging active or reactive power in mitigating frequency and/or voltage deviations. Finally, at the low level is the EVO that handles the short-term decisions of decentralising the functioning of an EV and essential power interfacing circuitry, as well as the generation of low-level switching functions. EVO level is a novel Power and Energy Management System (PEMS), which is further structured into three modular, hierarchical processes: Energy Management Shell (EMS), Power Management Shell (PMS), and Power Electronic Shell (PES). The shells operate chronologically with a different object and a different period term. Controlling the power electronics interfacing circuitry is an essential part of the integration of EVs into the microgrid within the EMS. A modified, multi-level, H-bridge cascade inverter without the use of a main (bulky) inductor is proposed to achieve good performance, high power density, and high efficiency. The proposed inverter can operate with multiple energy resources connected in series to create a synergized energy system. In addition, the integration of EVs into a simulated microgrid environment via a modified multi-level architecture with a novel method of Space Vector Modulation (SVM) by the PES is implemented and validated experimentally. The results from the SVM implementation demonstrate a viable alternative switching scheme for high-performance inverters in EV applications. The comprehensive simulation results from the MGO and CSO models, together with the experimental results at the EVO level, not only validate the distinctive functionality of each layer within a novel synergy to harness multiple energy resources, but also serve to provide compelling evidence for the potential of the proposed energy management and control framework in the design of future electric grids. The design framework provides an essential design to for grid modernisation.
Open Access
A novel quasi-dynamic guidance law for a dynamic dual-spin projectile with non-conventional, asymmetric roll constraints
(Sage, 2022-03-01) Norris, James; Economou, John T.; Hameed, Amer
A novel quasi-dynamic guidance law (QDGL) is presented for a dual-spin projectile (DSP) with unconventional constraints on roll direction. A 7 degree-of-freedom (DOF) dynamic model is established and the projectile operational mechanism is presented with a description of how it is used to enact control. The QDGL is presented and a parametric study is conducted to show how the QDGL parameters affect the system response. A procedure of using batches of Monte Carlo simulations is described, to numerically compare the system response with different QDGL configurations. A genetic algorithm is then used to optimise both the innate system parameters and PID controller gains. The disturbance rejection capabilities of the optimal QDGL are then evaluated along with the performance against different target profiles. It was found that the GA optimised QDGL is able to provide satisfactory control capabilities against static and dynamic targets.
Open Access
Power control, fault analysis and protection of series connected diode rectifier and VSC based MTDC topology for offshore application.
(2018-06) Abdul-Rahim, Ghaith Ali; Luk, Patrick Chi-Kwong; Economou, John T.
A multiterminal high-voltage dc (MTDC) system is a promising method for transmitting energy generated from an offshore windfarm (OWF). The creation of MTDC systems became easier by the introduction of voltage source converter (VSC) due to the flexibility and controllability it provides. This technology is newer than the line-commutated converter technology (LCC). Power systems can include any number of windfarms together with converters for both offshore and onshore power conversion. Therefore, this thesis suggests a three-terminal MTDC model of two offshore windfarms and one onshore inverter. The electric energy generated by the two windfarms is rectified into dc and transmitted to the shore using dc cable. Although a VSC or a diode rectifier (DR) can convert ac to dc, a series connection of a VSC and two DRs was proposed at the windfarm side to convert the generated power to achieve controllability of the uncontrollable diode rectifiers and reduces the high cost of badditional VSCs. The proposed topology converts the ac power by dividing the windfarm power so that one-third is the share of the VSC and two-thirds is the share of the DRs. The same topology is used to convert the power produced from the other windfarm. Then, the dc power is transmitted via an undersea dc cable to the onshore location, and is then inverted into ac before it is supplied to the neighbouring ac grid using a grid-side VSC. The proposed topology has many advantages, including a significant save in windfarm VSC (WFVSC) capital cost and a significant reduction in the loss of power of the converter without losing the overall controllability. However, although this topology is suitable for windfarm applications, it might not be suitable for high-voltage direct current (HVDC) that requires bidirectional power flow unless making changes to the topology such as disconnecting the diode rectifiers. Furthermore, fault analyses were investigated, including dc faults and ac faults. Ac faults are categorised as symmetrical or unsymmetrical faults. For comparison purposes, a Simulink model was designed, implemented, and simulated as a reference model. The reference model can operate as VSC-, DR-based MTDC, or a mix of both in a way that any component can be added to or removed from the model at any time during the simulation run. The contribution to the dc fault current from various parts such as dc capacitor and the adjacent feeder was investigated thoroughly, and detailed mathematical formulae were developed to compute fault current from these contributors. In addition, the results of the system response due to both fault types are illustrated and discussed. Both symmetrical and unsymmetrical ac faults were initiated on the onshore grid side, and the system response results are presented for those faults. A generalised control scheme (GCS) was proposed in this thesis, which add the ability the model to control the reactive power and is suitable for both balanced and unbalanced ac faults conditions. A protection against faults was investigated and implemented using dc circuit breakers. The protection system was built to ensure safe operation and to fulfil the grid code requirements. Many grid codes are available and presented in the literature, such as Spanish, British, and Danish; however, a grid code by E.ON was chosen. The protection scheme in VSC-based MTDC networks plays a vital role during dc faults. It is vital that this protection be sensitive, selective, fast, and reliable. Specifically, it must isolate the fault reliably from the system within a short time after the fault occurrence, while maintaining the remaining components of the system in a secure operational condition. For optimal performance, the protection scheme discussed in this thesis employs solid-state circuit breakers. A literature survey relevant to the tasks mentioned above was conducted.
Open Access
Quasi-real-time confined environment path generation for mobile robotic manipulator arms
(SAGE, 2018-01-10) Galvão Wall, David; Economou, John T.; Knowles, Kevin
Path generation for mobile robotic manipulator arms is challenging in dynamic environments because high-speed calculations are required to deal with fast-moving obstacles. A novel path-planning algorithm has been developed which solves in quasi-real time the problem of path generation in confined environments for interconnected multi-body systems, specifically a robotic manipulator arm with three links. The work presented in this article builds upon the previous work by reformulating the technique to increase the speed at which the algorithm is able to calculate a safe path. The complexity of the task space has increased substantially compared to previous work, and the algorithm has been reformulated to speed up the calculation in order to maintain or even improve its ability to plan a safe path in real time. The method is now able to calculate a safe path through environments significantly more quickly than the previous method, and the results presented in this article expand the complexity of the environment by a large amount and test the ability of the reformulated algorithm to still operate in real time, which the method achieves. It was found that the reformulated method reduces the calculation time for path generation exponentially when used to plan safe paths through test environments involving different numbers of obstacles. The new algorithm thus has the potential to facilitate path planning in challenging dynamic environments, such as those used in sensitive manufacturing and maintenance tasks as well as bomb disposal and similar applications.
Open Access
A review of dual-spin projectile stability
(Elsevier, 2019-06-06) Norris, James; Hameed, Amer; Economou, John T.; Parker, Simon
This paper gives a succinct review of dual-spinprojectile stability and some technologies relating to them. It describes how the traditional stability factors from linear projectile theory are modified to better describe a controlled dual-spin projectile. Finally, it reviews works which have investigated how different aspects of a controlled dual-spin design can affect flight stability, primarily airframe structure and canard properties. A conclusion is given, highlighting important guidelines from the enclosed discussions