George van Schoor

A Two-Dimensional Analytic Thermal Model for a High-Speed PMSM Magnet

Permanent-magnet synchronous machines (PMSMs) are well suited for high-speed (HS) applications due to their high efficiency, power density, and dynamic response capability. The heat extraction area decreases as the speed increases, making thermal effects more dominant at high speed. The temperature-dependent properties of permanent magnets necessitate high-detail thermal models. This paper presents a 2-D analytical model for a HS PMSM magnet. The diffusion equation is solved where three of the PM boundaries experience convection heat flow; as the case is in radial flux machines. The heat generated on the rotor surface due to eddy currents is also taken into account. The model is verified using numerical techniques and shows good correlation (within 1.5%). The model is also validated through experiments performed on a 4 kW, 30 000 r/min PMSM.

Thermal modelling of a high speed permanent magnet synchronous machine

The thermal behaviour of permanent magnet synchronous machines (PMSMs) is important since overheating of the permanent magnets can lead to demagnetization. This article gives an overview of a hybrid thermal model for a high speed PMSM which combines lumped parameter and analytical models. The losses found in a slotless PMSM are also discussed since they are the heat sources. An overview of the experiments performed to determine some of the thermal parameters and verify the models are also given. It is shown that bearing loss can make a significant contribution to the thermal behavior of a machine.

Predictive PID Control of Non-Minimum Phase Systems

Control engineers have been aware of non-minimum phase systems showing either undershoot or time-delay characteristics for some considerable time (Linoya & Altpeter, 1962; Mita & Yoshida, 1981; Vidyasagar, 1986; Waller & Nygardas, 1975). A number of researchers that addressed this problem from a predictive control point of view mainly followed one of two approaches: a classical (non-optimal) predictive approach or a modern optimisation based predictive approach (Johnson & Moradi, 2005). The common characteristic of all these approaches is that they are model-based. Predictive control allows the controller to predict future changes in the output signal and to use this prediction to generate a desirable control variable. The classical predictive controllers that are most widely considered include the Smith predictor structure and the internal model control (IMC) structure (Katebi & Moradi, 2001; Morari & Zafiriou, 1989; Tan et al., 2001). Modern predictive controllers consider generalised predictive control (GPC) or model-based predictive control (MPC) structures (Johnson & Moradi, 2005; Miller et al., 1999; Moradi et al., 2001; Sato, 2010). The performance of a PID controller degrades for plants exhibiting non-minimum phase characteristics. In order for a PID controller to deal with non-minimumphase behaviour, some kind of predictive control is required (Hagglund, 1992). Normally the derivative component of the PID controller can be considered as a predictive mechanism, however this kind of prediction is not appropriate when addressing non-minimum phase systems. In such a case the PI control part is retained and the prediction is performed by an internal simulation of plant inside the controller. This chapter starts with a quick review of the system-theoretic concept of a pole and zero and then draws the relationship to non-minimum phase behaviour. The relationship between the undershoot response and time-delay response will be discussed using Pade approximations. Classical and modern predictive PID control approaches are considered with accompanying examples. The main contribution of the chapter is to illustrate the context and categories of predictive PID control strategies applied to non-minimum phase systems by:

A study of the loss characteristics of a single cell PEM electrolyser for pure hydrogen production

In this paper the losses of a proton exchange membrane (PEM) single cell electrolyser were investigated. The ohmic, activation and mass transfer losses are the most prominent losses in a PEM electrolyser. The Electrochemical Impedance Spectroscopy (EIS) method was applied to identify these losses. A parametric study of each loss component was performed by changing a component or condition responsible for the loss. The membrane thickness was varied in the Membrane Electrode Assembly (MEA) to identify the ohmic loss and the temperature was changed to capture the activation loss. Two different diffusion media were used to investigate the mass transfer effect. The results were confirmed with polarisation curves and Tafel plots.

An Energy Perspective on Modelling, Supervision, and Control of Large-Scale Industrial Systems: Survey and Framework

Abstract Energy is a universal concept that can be used across physical domains to describe complex large-scale industrial systems. This brief survey and framework gives a perspective on energy as a unifying domain for system modelling, supervision, and control. Traditionally, modelling and control problems have been approached by adopting a signal-processing paradigm. However, this approach becomes problematic when considering non-linear systems. A behavioural viewpoint, which incorporates energy as basis for modelling and control, is considered a viable solution. Since energy is seen as a unifying concept, its relationship to Euler-Lagrange equations, state space representation, and Lyapunov functions is discussed. The connection between control and process supervision using passivity theory coupled with a system energy balance is also established. To show that complex industrial systems comprising multiple energy domains can be modelled by means of a single electric circuit, its application to a large-scale thermo-hydraulic system is presented. Next, a simple non-linear transmission impedance electric circuit is used to illustrate how energy can be used to not only describe a system, but also serve as basis for system optimisation. An energy-based framework is proposed whereby energy is used as a unifying domain to work in, to analyse, and to optimise large-scale industrial systems.

A self-sensing active magnetic bearing based on a direct current measurement approach

Active magnetic bearings (AMBs) have become a key technology in various industrial applications. Self-sensing AMBs provide an integrated sensorless solution for position estimation, consolidating the sensing and actuating functions into a single electromagnetic transducer. The approach aims to reduce possible hardware failure points, production costs, and system complexity. Despite these advantages, self-sensing methods must address various technical challenges to maximize the performance thereof. This paper presents the direct current measurement (DCM) approach for self-sensing AMBs, denoting the direct measurement of the current ripple component. In AMB systems, switching power amplifiers (PAs) modulate the rotor position information onto the current waveform. Demodulation self-sensing techniques then use bandpass and lowpass filters to estimate the rotor position from the voltage and current signals. However, the additional phase-shift introduced by these filters results in lower stability margins. The DCM approach utilizes a novel PA switching method that directly measures the current ripple to obtain duty-cycle invariant position estimates. Demodulation filters are largely excluded to minimize additional phase-shift in the position estimates. Basic functionality and performance of the proposed self-sensing approach are demonstrated via a transient simulation model as well as a high current (10 A) experimental system. A digital implementation of amplitude modulation self-sensing serves as a comparative estimator.

Control of magnetically suspended rotor combined with motor drive system

Abstract This paper presents the cooperative control between the active magnetic bearing system and the permanent magnet synchronous drive. More specifically, the coupling between the vibration control and sensorless drive control is considered since both systems have the ability to estimate the angular speed. The coupling of the estimated speed in each controller is considered. Also, a modified start-up procedure for the sensorless vector control had to be developed when the drive is combined with the AMB system to accommodate the low friction which does not yield damping of the speed perturbation at start-up. Simulation results are presented for the developed control using detailed models for both systems.

Equivalent electrical circuit modelling of a Proton Exchange Membrane electrolyser based on current interruption

A Proton Exchange Membrane (PEM) electrolyser is characterised and modelled to identify important electrochemical effects. These electrochemical effects include the ohmic, activation, and concentration losses within the PEM electrolyser during hydrogen production. The electrochemical effects of the PEM electrolyser are modelled by means of equivalent electrical circuits. The equivalent electrical circuit components of importance are the membrane resistance, the charge transfer resistance, the double layer capacitance and the Warburg impedance. The current interrupt method is proposed by using, (i) the natural voltage response method and (ii) system identification, for solving the parameters of the equivalent electrical circuits. In this paper both simulation and experimental results are provided.

Block RAM Implementation of a Reconfigurable Real-time PID Controller

Despite the numerous advantages reconfigurable computing adds to a system, it is only advantageous if the execution time exceeds the configuration time. As a result of the long configuration time, reconfiguration is only suitable for quasi-static applications. Due to the additional overhead required for communication, the bus-based architectures most commonly used to connect the configuration controller to the memory contribute to the configuration time. A method proposed to ameliorate this overhead is an architecture utilizing localized block RAM (BRAM), directly connected to the configuration controller to store the configuration data. The drawback of this method is that the BRAM is extremely limited and only a discrete set of configurations can be stored. This paper is a work in progress and proposes a hardware reconfiguration architecture that addresses the size limitation of the localized BRAM-architecture by using parameterizable configuration. This will allow a single bitstream stored in the BRAM to be specialized according to certain parameters, which will be used to reconfigure the device. This will migrate reconfigurable computing to more dynamic applications. The architecture proposed in this paper will be validated using real-time PID control of a five degree of freedom active magnetic bearing system.

Empirical Parameter Identification for a Hybrid Thermal Model of a High-Speed Permanent Magnet Synchronous Machine

An accurate thermal model will commonly require empirical parameter identification, specifically for the convection coefficients and interface resistances. A high-speed permanent magnet synchronous machine test platform, equipped with various temperature and power measuring equipment, is used to determine these parameters. Specifically, two tests, a dc injection test and rotational test with no load connected, were performed. The results were compared with a lumped thermal model and the parameters updated until an acceptable match was achieved. There were significant differences in the temperature rise when activating forced air cooling, thus significantly influencing the convection coefficients. Also, a significant difference in the interface resistances showed that in these high-speed machines, doing only the dc injection test will not give accurate interface resistance values. The work is novel through combining systematic empirical parameter identification to determine the convection coefficients and interface resistances for a machine where the end windings are cooled by forced tangential air flow.