Fault Detection in Surface PMSM with Applications to Heavy Hybrid Vehicles

This report explores detecting inter-turn short circuit (ITSC) faults in surface permanent magnet synchronous machines (SPMSM). ITSC faults are caused by electrical insulation failures in the stator windings and can lead to shorts to ground and even fires. This report proposes methods for detecting these faults using a moving horizon observer (MHO) to reduce the chance of electrical shocks and fires. Specifically, this report constructs a MHO for ITSC fault detection in SPMSM. ITSC fault tolerant control is investigated for a 2004 Toyota Prius hybrid vehicle having a traction SPMSM. Once the supervisory-level powertrain power flow control becomes aware of the presence of a fault and its degree from the MHO, the control (i) reduces the maximum possible vehicle speed to ensure SPMSM thermal constraints are not violated and (ii) switches to a traction motor input-output power efficiency appropriate for the degree of fault. These steps are taken during a fault rather than shutting down the traction motor to provide a “limp home” capability. The traction motor cannot simply be turned off because its rotation is not independent of drive wheel rotation. The control is demonstrated by simulating the Prius over a 40 s drive velocity profile with faults levels of 0.5%, 1%, 2%, and 5% detected at the midpoint of the profile. For comparison, the Prius is also simulated without a traction motor fault. Results show that the control reduced vehicle velocity upon detection of a fault to appropriate safe values. Further, the challenges of ITSC fault tolerant control for heavy hybrid vehicles are examined. This work is partially supported by the Department of Energy, Award No. DE-EE0005568. The authors would like to acknowledge the support of Greg Shaver and the Hoosier Heavy Hybrid Center of Excellence. S. Johnson, R. DeCarlo, and S. Pekarek are with the Department of Electrical and Computer Engineering at Purdue University, 610 Purdue Mall, West Lafayette, IN 47907 (email: [email protected], [email protected], [email protected]). R. Meyer is with the Department of Mechanical and Aerospace Engineering at Western Michigan University, 1903 West Michigan Avenue, Kalamazoo, MI 49008 (email: [email protected])

Optimal control of robotic systems with logical constraints: Application to UAV path planning

Abstract-Optimal control of robotic systems with logical constraints is an instance of a hybrid optimal control problem. It has been traditionally treated as a mixed-integer programming problem (MIP) which is of combinatorial complexity. This paper proposes a new approach for transforming logical constraints into inequality and equality constraints involving only continuous variables. In this way the hybrid optimal control problem is converted to a smooth optimal control problem that can in turn be solved using traditional nonlinear programming methods, thereby dramatically reducing the computational complexity of finding the solution. We illustrate the techniques by solving an optimal path planning problem for multiple unmanned aerial vehicles (UAVs) with collision avoidance. Simulation results are given to show the effectiveness of the approach

Gas Turbine Engine Behavioral Modeling

This paper develops and validates a power flow behavioral model of a gas tur- bine engine with a gas generator and free power turbine. “Simple” mathematical expressions to describe the engine’s power flow are derived from an understand- ing of basic thermodynamic and mechanical interactions taking place within the engine. The engine behavioral model presented is suitable for developing a supervisory level controller of an electrical power system that contains the en- gine connected to a generator and a large interconnection of many components, e.g., a naval ship power system powered by gas turbine engines. First principles engine models do not lend themselves to the preceding control development be- cause of their high granularity. The basis of the behavioral model development is the balance of energy flow across engine components; power flow is obtained by taking the time derivative of the energy flow. The behavioral model of a spe- cific engine utilizes constants and empirical fits of power conversion efficiencies obtained from data collected from a high-fidelity engine simulator. Behavioral models for a GE LM2500 and an engine similar to a GE T700 are constructed; the 2-norm normalized error between the simulator and behavioral model out- puts for both engines is 3.5% or less

Linear circuit analysis / time domain, phasor, and laplace transform approaches

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Commande d'un réseau électrique comportant un lien en courant continu

Synthèse de la commande -- Résultats de la simulation -- Control formulation -- The component connection method -- Continuations approach for local controllers design -- Under appropriate assumptions -- Computational considerations and assumptions -- Robustness considerations -- Two-terminal system -- Results obtained -- Objective of the control -- Modulation strategy -- Modulation designs -- Analog simulation