Fault-Tolerant Control of a Dual-Stator PMSM for the Full-Electric Propulsion of a Lightweight Fixed-Wing UAV

The reliability enhancement of electrical machines is one of the key enabling factors for spreading the full-electric propulsion to next-generation long-endurance UAVs. This paper deals with the fault-tolerant control design of a Full-Electric Propulsion System (FEPS) for a lightweight fixed-wing UAV, in which a dual-stator Permanent Magnet Synchronous Machine (PMSM) drives a twin-blade fixed-pitch propeller. The FEPS is designed to operate with both stators delivering power (active/active status) during climb, to maximize performances, while only one stator is used (active/stand-by status) in cruise and landing, to enhance reliability. To assess the fault-tolerant capabilities of the system, as well as to evaluate the impacts of its failure transients on the UAV performances, a detailed model of the FEPS (including three-phase electrical systems, digital regulators, drivetrain compliance and propeller loads) is integrated with the model of the UAV longitudinal dynamics, and the system response is characterized by injecting a phase-to-ground fault in the motor during different flight manoeuvres. The results show that, even after a stator failure, the fault-tolerant control permits the UAV to hold altitude and speed during cruise, to keep on climbing (even with reduced performances), and to safely manage the flight termination (requiring to stop and align the propeller blades with the UAV wing), by avoiding potentially dangerous torque ripples and structural vibrations

Fault-Tolerant Control of a Three-Phase Permanent Magnet Synchronous Motor for Lightweight UAV Propellers via Central Point Drive

This paper deals with the development and the performance characterization of a novel Fault-Tolerant Control (FTC) aiming to the diagnosis and accommodation of electrical faults in a three-phase Permanent Magnet Synchronous Motor (PMSM) employed for the propulsion of a modern lightweight fixed-wing UAV. To implement the fault-tolerant capabilities, a four-leg inverter is used to drive the reference PMSM, so that a system reconfiguration can be applied in case of a motor phase fault or an inverter fault, by enabling the control of the central point of the three-phase connection. A crucial design point is to develop Fault-Detection and Isolation (FDI) algorithms capable of minimizing the system failure transients, which are typically characterized by high-amplitude high-frequency torque ripples. The proposed FTC is composed of two sections: in the first, a deterministic model-based FDI algorithm is used, based the evaluation of the current phasor trajectory in the Clarke’s plane; in the second, a novel technique for fault accommodation is implemented by applying a reference frame transformation to post-fault commands. The FTC effectiveness is assessed via detailed nonlinear simulation (including sensors errors, digital signal processing, mechanical transmission compliance, propeller loads and electrical faults model), by characterizing the FDI latency and the post-fault system performances when open circuit faults are injected. Compared with reports in the literature, the proposed FTC demonstrates relevant potentialities: the FDI section of the algorithm provides the smallest ratio between latency and monitoring samples per electrical period, while the accommodation section succeeds in both eliminating post-fault torque ripples and maintaining the mechanical power output with negligible efficiency degradation

Teaching Learning Based Optimization (TLBO) algorithm for trajectory planning of a quadrotor in an urban environment.

Most of the optimization algorithms are characterized by a large number of parameters that must be well tuned to have a good working algorithm. This limitation is avoided in Teaching-Learning-Based Optimization (TLBO) algorithm, where a few numbers of parameter needs to be well settled. TLBO is a recent developed evolutionary algorithm based on two elementary concepts of education, namely teaching phase and learning phase. At first, learners improve their knowledge through the teaching methodology of teacher and finally learners increase their knowledge by interactions among themselves. Lately, the TLBO algorithm has been widely used in the scientific fields and compared with the other existing technique it demonstrates its superiority. Despite this, few applications of the method to the trajectory planning problem have been made. Two different problem have been addressed using the proposed TLBO method in this work. A simple trajectory planning problem for a terrestrial vehicle and trajectory planning problem for a quadrotor in urban environment. Literature investigation shows that the modelling work in trajectory planning through TLBO technique, especially on delivery task in urban environment, is insufficient. Hence, the validity of TLBO algorithm in solving trajectory planning problem with multiple constraints need to be still verified. The principles of TLBO algorithm are described first, and how TLBO algorithm is integrated into the trajectory planning problem is further explained. First, the dynamic, the constraints and the goals is presented for a terrestrial vehicle. Results show that in order to get optimal solutions, with satisfied constraints, the TLBO’s parameters have to be well settled. It means the parameters have to be tuned in a way that the number of discarded solutions, due to the constraints, are minimized. Hence, TLBO’s parameters must be as much as possible close to the one that reflect a real situation. It can be concluded that m_subjects=5 and n_students=40 can result in solutions good enough in this problem. Second, the dynamic of quadrotor, the constraints of quadrotor manoeuvrability, urban environment and delivery task are considered in the trajectory planning model, and the goals are to minimize the deviation between the destination targets and the relative quantities at the quadrotor final position. To test the proposed algorithm three different scenarios are analysed, which represent the main phase of a delivery task: Take-off cruise path, cruise path and landing path. Results show that, once the TLBO’s parameters are well settled, the algorithm is able to reach the targets with respect to all the constraints. In particular for the first two phases of the trajectory the TLBO’s parameters match; for the landing phase a reduction of the control variable u_1 must be realized. This represent a well settling procedure of the parameters, indeed in a real landing situation a reduction of the range power is realized. In the future, there are different constraints and target that could be considered. As no constraint on the control inputs rate are taken into account in this work, the obtained control input can result in an over power consumption considering that the energy requested by the vehicle during the mission is ∝(ω ̇_i (t),ω_i^2 (t),ω_i (t))∙ω_i (t) as reported in literature. Hence, a third cost function should be added in order to generate trajectories with minimum energy. Besides, also the wind can affect the energy consumption, a much real environment could be realized therefore adding a wind field

Diagnosis of power switch faults in three-phase permanent magnet synchronous motors via current-signature technique

The paper deals with the development of a model-based current-signature algorithm for the detection and isolation of power switch faults in three-phase Permanent Magnet Synchronous Motors (PMSMs). The algorithm, by elaborating the motor currents feedbacks, reconstructs the current phasor trajectories in the Clarke plane through elliptical fittings, up to detecting and isolating the fault depending on the characteristics of the signature deviation from the nominal one. As a rough approximation, as typically proposed in the literature, the fault of one out of six power switches implies that, at constant speed operation, the phasor trajectory deviates from the nominal circular path up to a semi-circular “D-shape” signature, the inclination of which depends on the failed converter leg. However, this evolution can significantly deviate in practical cases, due to the dynamics related to the transition of motor phase connections from failed to active switches. The study demonstrates that an online ellipse fitting of the current signature can be effective for diagnosis, through correlating the ellipse centre to the location of the failed switch. The performances of the proposed monitoring technique are here assessed via the nonlinear simulation of a PMSM employed for the propulsion of a lightweight fixed-wing Unmanned Aerial Vehicle (UAV), by quantifying the fault latencies and the related transients

Condition monitoring of the torque imbalance in a dual-stator permanent magnet synchronous motor for the propulsion of a lightweight fixed-wing UAV

This paper deals with the development of a model-based technique to monitor the condition of torque imbalances in a dual-stator permanent magnet synchronous motor for UAV full-electric propulsion. Due to imperfections, degradations or uncertainties, the torque split between power lines can deviate from the design, causing internal force-fighting and reduced efficiency. This study demonstrates that, by only elaborating the measurements of speed and direct/quadrature currents of the stators during motor acceleration/deceleration, online estimations of demagnetization and electrical angle misalignment can be obtained, thus permitting the evaluation of the imbalance and total torque of the system. A relevant outcome is that the technique can be used for developing both signal-based and model-based monitoring schemes. Starting from physical first-principles, a nonlinear model of the propulsion system, including demagnetization and electrical angle misalignment, is developed in order to analytically derive the relationships between monitoring inputs (currents and speed) and outputs (degradations). The model is experimentally validated using a system prototype characterized by asymmetrical demagnetization and electrical angle misalignment. Finally, the monitoring effectiveness is assessed by simulating UAV flight manoeuvres with the experimentally-validated model: injecting different levels of degradations and evaluating the torque imbalance

Heuristic estimation of temperature-dependant model parameters of Li-Po batteries for UAV applications

This work deals with the system identification of Thevenin models of Li-Po batteries for UAV applications. Starting from the results of an experimental hybrid pulse-power characterization of a battery pack carried out at different temperatures (0°C, 15°C, 49°C) and within the operative range of state-of-charge (>10%), the model parameters are identified via three heuristic optimization algorithms, based on particle-swarm, teaching-learning and differential evolution techniques. Differently from conventional approaches typically applied by commercial CAE tools (e.g. Matlab), the proposed techniques are directly applied to the whole time history of the measurements. The results highlight that the particle-swarm method exhibits the fastest convergence, but it requires to initially define the algorithm weighing coefficients. This is not needed for teaching-learning based optimization, but computational effort strongly increases to achieve satisfactory accuracy. The differential evolution technique provides intermediate performances, especially if the total computation time is also considered. The case study is referred to the 1850 mAh/6 cells/22.2 V Li-Po battery pack employed in the lightweight fixed-wing UAV Rapier X-25, developed by Sky Eye Systems (Italy)

Development and Experimental Validation of Novel Thevenin-Based Hysteretic Models for Li-Po Battery Packs Employed in Fixed-Wing UAVs

Lithium batteries employed in lightweight fixed-wing UAVs are required to operate with large temperature variations and, especially for the emerging applications in hybrid propulsion systems, with relevant transient loads. The detailed dynamic modelling of battery packs is thus of paramount importance to verify the feasibility of innovative hybrid systems, as well as to support the design of battery management systems for safety/reliability enhancement. This paper deals with the development of a generalised approach for the dynamic modelling of battery packs via Thevenin circuits with modular hysteretic elements (open circuit voltage, internal resistance, RC grids). The model takes into account the parameters’ dependency on the state of charge, temperature, and both the amplitude and sign of the current load. As a relevant case study, the modelling approach is here applied to the Li-Po battery pack (1850 mAh, 6 cells, 22.2 V) employed in the lightweight fixed-wing UAV Rapier X-25 developed by Sky Eye Systems (Cascina, Italy). The procedure for parameter identification with experimental measurements, obtained at different temperatures and current loads, is firstly presented, and then the battery model is verified by simulating an entire Hybrid Pulse Power Characterisation test campaign. Finally, the model is used to evaluate the battery performance within the altitude (i.e., temperature) envelope of the reference UAV. The experiments demonstrate the relevant hysteretic behaviour of the characteristic relaxation times, and this phenomenon is here modelled by inserting Bouc–Wen hysteresis models on RC grid capacitances. The maximum relative error in the terminal output voltage of the battery is smaller than 1% for any value of state of charge greater than 10%

Climbing performance enhancement of small fixed-wing UAVs via hybrid electric propulsion

The climb rate and climb gradient of small fixed-wing Unmanned Aerial Vehicles (UAVs), characterized by extremely compact and lightweight design, are typically limited by the maximum allowable temperature of the engine cylinder head, especially in hot environment conditions. The problem is often overcome by alternating climb and levelled flight phases to let the engine cool down, but the resulting performances are far from satisfactory. This paper aims to evaluate the feasibility of a reconfigurable hybrid propulsion system based on the integration of the UAV internal combustion engine with its electric generator, temporarily (during climb) converted into motor and supplied by the battery pack, to maintain/boost the propeller thrust while reducing the combustion engine temperature. With reference to the lightweight surveillance UAV Rapier X-25 (maximum take-off weight up to 25 kg) by Sky Eye Systems (Italy), a detailed nonlinear model of the reconfigurable hybrid propulsion system is developed and coupled with the models of the propeller and the vehicle flight dynamics. The system dynamic performances during severe climb manoeuvres are thus characterized, by demonstrating that the proposed solution can both improve the UAV climb rate and, by reducing the combustion engine power request, limit the temperature increase of the cylinder head

Experimental characterisation of Li-Po battery packs and BLDC machines for hybrid propulsion systems of lightweight UAVs

This paper deals with the design and the implementation of experiments for the performance characterisation of the main power devices of the hybrid propulsion system of a lightweight fixed-wing UAV. The basic objective of the work is to identify the parameters of the three-phase brushless DC machine (BLDCM) model and the battery pack model, up to support the development of a virtual prototype of the hybrid propulsion system, to be used for the system design and validation. In particular, the experiments are designed to identify the BLDCM model in terms of resistance, inductance, and back-electromotive force waveforms as functions of the motor angle, as well to define the parameters of the Thevenin model of the battery pack (open-circuit voltage, internal and polarization resistances, battery capacitance) as functions of battery state-of-charge and environmental temperature in the range from 0 to 49 °C