Efficiency and time-optimal control of fuel cell - compressor - electrical drive systems

The proton exchange membrane fuel cell (PEMFC) based power generation sys- tem is regarded as one of the perspective energy supply solutions for a wide variety of applications including distributed power plants and transport. The main compo- nent of the FC system is the FC stack, where the process of electrochemical energy conversion takes place. Additionally, such systems usually contain an auxiliary compression subsystem which supplies the reactant gases to the FC stack as well as maintains certain operation conditions: pressure, temperature, humidity, etc. The proper operation of the compression system signi¯cantly improves the performance characteristics of the total system. On the other hand, it consumes a portion of the electrical energy produced, thus reducing the net e±ciency of the total system. This thesis focuses on an innovative way to improve both the energy e±ciency and the response characteristics of a power generation system with a PEMFC. The approach principally consists of the control of the air compressor powered by the electrical drive. This method could be considered as an alternative to a redesign of the complete system (changing the power level, using an extra energy bu®er, etc). The modern high-speed centrifugal compressor has been regarded as one of the best candidates for the FC system. It has appropriate characteristics with respect to e±ciency, reliability, compact design, etc. However, the presence of a stability margin or so-called "surge line" limits its operation area. With the aim to overcome this constraint, a novel active surge suppression approach has been proposed for application in the system. This control method relies on the high-performance speed control of the electrical drive and accurate measurement and estimation of the thermodynamic quantities, such as air pressure and mass °ow. The choice of an induction motor drive has been justi¯ed by its commonly known advantages: low cost, simple construction, high reliability, etc. These features be- come especially important in high-speed applications. For the detailed investigation and performance prediction of the prime mover, a global electromagnetic design pro- cedure with thermal analysis of a high-speed induction motor has been performed. The obtained analytical results have been veri¯ed numerically by a high-precision Finite Elements Method. A good agreement between the analytical and FEM simu- lation results has been achieved. The mentioned active surge control in combination with the high-performance ¯eld-oriented control of the induction motor has been im- plemented and tested. The test bench comprises the centrifugal compressor with the PVC piping system, the high-speed induction motor drive, the real-time data acquisition and the control system. The experimental results proved the e®ective- ness of the active surge suppression by means of the drive torque actuation: the operation point of the compressor can be moved beyond the surge line while the process remains stable. Using the combined mathematical models of the FC stack, the centrifugal com- pressor and the ¯eld-oriented controlled induction motor drive, the static and dy- namic behavior of the total system have been simulated, allowing to clarify the interaction between the electrochemical processes in the FC stack, the thermody- namic processes in the compression system and the electromechanical performance of the drive. Various system operating regimes have been proposed and analyzed. When the FC electrical load changes frequently and fast, the constant-speed operating regime can be used. In case of a slow variation of the FC electrical load, the variable- speed operating regime is advisable, providing a high energy e±ciency at low FC load. In intermediate cases, the load-following-mass °ow operating regime with the application of the active surge control of the compressor becomes preferable. This operating regime eliminates the relatively long mechanical transient process, keep- ing the energy consumption of the balance of plant (BoP) approximately linearly proportional to the main load. The operating regime with applied linear quadratic Gaussian (LQG) time-optimal control has been proposed as an alternative to the load-following-mass °ow operating regime and the variable-speed operating regime. The transition between two steady-state operating points, where the system e±- ciency is maximum, follows the time-optimal trajectory, keeping the transient re- sponse time small. Finally, recommendations for further research have been formulated concerning the dynamic response and energy-e±ciency of a fuel cell system. Mainly, the recom- mendations concern further improvements of presented control strategies and their more comprehensive experimental veri¯cation using a complete FC system. First of all, the use of a direct induction motor drive for the compressor stabiliza- tion would signi¯cantly improve the e®ectiveness of the surge control. It would allow to control the surge of higher frequency, or to stabilize the compressor operation at larger distance from the surge line. Second, a combination of the electrical drive torque control with a valve position control would result probably in a more e®ective surge control, together with fast transients of the system operating point. Third, the application of the electrical drive for the compressor active surge control in a FC system would require new control algorithms for energy-e±ciency improvement of the induction motor, not compromising its high-performance capa- bilities

Speed Control of a Multi-Motor System Based on Fuzzy Neural Model Reference Method

The direct-current (DC) motor has been widely utilized in many industrial applications, such as a multi-motor system, due to its excellent speed control features regardless of its greater maintenance costs. A synchronous regulator is utilized to verify the response of the speed control. The motor speed can be improved utilizing artificial intelligence techniques, for example fuzzy neural networks (FNNs). These networks can be learned and predicted, and they are useful when dealing with nonlinear systems or when severe turbulence occurs. This work aims to design an FNN based on a model reference controller for separately excited DC motor drive systems, which will be applied in a multi-machine system with two DC motors. The MATLAB/Simulink software package has been used to implement the FNMR and investigate the performance of the multi-DC motor. moreover, the online training based on the backpropagation algorithm has been utilized. The obtained results were good for improving the speed response, synchronizing the motors, and applying load during the work of the motors compared to the traditional PI control method. Finally, the multi-motor system that was controlled by the proposed method has been improved where its speed was not affected by the disturbance. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Taif University, TU: TURSP-2020/211Funding: This research was funded by Taif University, project number (TURSP-2020/211), Taif University, Taif, Saudi Arabia

Analysis and simulation of the high-speed torque performance of brushless D.C. motor drives

PhD ThesisThe work presented in this thesis is concerned with the analysis, modelling, simulation and control of a surface mounted permanent magnet motor supply by a voltage controlled Pulse-Width Modulation (PWM) inverter. In Chapter 1 an overall description of the design and construction of individual components of the brushless dc drive system is presented along with a review of the general concept of the drive system. This type of machine is compared with other types of machine and the potential advantages of this new concept, both technical and economic, outlined. In Chapter 2 the operation and the control aspects of the brushless dc motor are described, with particular emphasis placed on the basic requirements for the operation, torque production, performance characteristic and control. The high-speed torque control methods are also described and their merits are reviewed. In addition the effects of different parameters of machine design on the torque-speed characteristics are discussed. Chapter 3 elaborates on the analysis and simulation work by presenting a comprehensive analysis which aims to show that direct three-phase representation can be used as an effective tool for performance assessement of brushless dc drive systems operating over a wide speed range. In Chapter 4 the performance of the brushless dc motor supplied by a PWM inverter with a view to improving the high-speed torque performance is investigated. Simulation and analysis of the brushless dc motor is presented in which the actual parameters of the experimental machine are used. The aim of the analysis is to simulate a brushless d. c. drive system operating in closed-loop control modes, which use high speed torque control techniques in conjunction with a PWM control technique. A detailed analytical model which makes possible the use of machine theory for representing the performance of the brushless dc motor is presented in Chapter 5. The method utilizes the phasor diagram, where machine performance in terms of the main control variables such as voltage and phase advance angle is demonstrated. Chapter 5 also presents an analytical expression for the phase-advance angle which yields maximum torque at a given motor speed. An analytical study concerning the optimum phase advance is developed in Chapter 6. In this work two analytical approaches to the problem of obtaining an optimum phase advance angle are presented. Chapter 6 presents a detailed analysis of the shape of the current and back-emf waveforms in a trapezoidal brushless dc motor drive and their effects on the torque/speed performance. Chapter 7 presents the implementation of a microprocessor based system, which can set the phase advance angle to its optimum value at any motor speed. This implementation is done in real time on the protortype drive using a TMS320C30 digital signal processor. Features of the method proposed in this thesis include the estimation algorithms for predicting the time advance. Experimental results on a drive system demonstrate the satisfactory performance of both the hardware and software of the control scheme

Online loss minimization based direct torque and flux control of IPMSM drive

With the advent of high energy rare earth magnetic material such as, third generation neodymium-iron-boron (NdFeB), permanent magnet synchronous motor (PMSM) is becoming more and more popular in high power industrial applications (e.g., high-speed railway) due to its advantageous features such as high energy density, stable parameters, high power factor, low noise and high efficiency as compared to the conventional ac motors. Over the years, vector control and direct torque and flux control (DTFC) techniques have been used for high performance motor drives. But, the DTFC is faster than that of conventional vector control as the DTFC scheme doesn't need any coordinate transformation, pulse width modulation (PWM) and current regulators. The DTFC utilizes hysteresis band comparators for both flux and torque controls. Most of the past researches on DTFC based motor drives mainly concentrated on the development of the inverter control algorithm with less torque ripple as it is the major drawback of DTFC. The torque reference value is obtained online based on motor speed error between actual and reference values through a speed controller. Traditionally, researchers chose a constant value of air-gap flux reference based on trial and error method which may not be acceptable for high performance drives as the air-gap flux changes with operating conditions and system disturbance. Efficient high performance drives require fast and accurate speed response to cope with disturbances and algorithm to minimize motor losses. However, if the reference air-gap flux is maintained constant it is not possible to control the motor losses. Therefore, this thesis presents a novel loss minimization based DTFC scheme for interior type PMSM drive so that the drive system can maintain both high efficiency and high dynamic performance. An online model based loss minimization algorithm (LMA) is developed to estimate the air-gap flux so that the motor operates at minimum loss condition while taking the general advantages of DTFC over conventional vector control. The performance the proposed LMA based DTFC for PMSM drive is tested in both simulation and real-time implementation at different operating conditions. The results verify the effectiveness of the proposed flux observer based DTFC scheme for PMSM drive

The Detection of Shaft Misalignments using Motor Current Signals from a Sensorless Variable Speed Drive

Shaft misalignments are common problems in rotating machines which cause additional dynamic and static loads, and vibrations in the system, leading to early damages and energy loss. It has been shown previously that it is possible to use motor current signature analysis to detect and diagnose this fault in motor drives. However, with a variable speed drive (VSD) system, it becomes dif-ficult to detect faults as the drive compensates for the small changes from fault ef-fects and increased noise in the measured data. In this paper, motor current signa-tures including dynamic and static data have been investigated for misalignment diagnosis in a VSD system. The study has made a systemic comparison of differ-ent control parameters between two common operation modes: open loop and sen-sorless control. Results show that fault detection features on the motor current from the sensorless mode can be the same as those of the open loop mode, however, the detection and diagnosis is significantly more difficult. In contrast, because of the additional frictional load, features from static data show results of early detection and diagnosis of different degrees of misalignment is as good as that from conventional vibration methods

Design and development of a solar array drive

The design and development of a dry lubricated direct drive solar array pointing mechanism is discussed for use on the Orbital Test Satellite (OTS), MAROTS, European Communication Satellite (ECS), and others. Results of life testing the original prototype and the OTS mechanism are presented together with an appraisal of expected future development

Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor

Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm for building efficient neural network based architectures for control of fast and agile robots. In this paper, we present a spiking neural network architecture that uses sensory feedback to control rotational velocity of a robotic vehicle. When the velocity reaches the target value, the mapping from the target velocity of the vehicle to the correct motor command, both represented in the spiking neural network on the neuromorphic device, is autonomously stored on the device using on-chip plastic synaptic weights. We validate the controller using a wheel motor of a miniature mobile vehicle and inertia measurement unit as the sensory feedback and demonstrate online learning of a simple 'inverse model' in a two-layer spiking neural network on the neuromorphic chip. The prototype neuromorphic device that features 256 spiking neurons allows us to realise a simple proof of concept architecture for the purely neuromorphic motor control and learning. The architecture can be easily scaled-up if a larger neuromorphic device is available.Comment: 6+1 pages, 4 figures, will appear in one of the Robotics conference

A circular model for song motor control in Serinus canaria

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.Fil: Alonso, Rodrigo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Trevisan, Marcos Alberto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Goller, Franz. University Of Utah. Department Of Biology; Estados UnidosFil: Mindlin, Bernardo Gabriel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Design of a five-axis ultra-precision micro-milling machine—UltraMill. Part 1: Holistic design approach, design considerations and specifications

High-accuracy three-dimensional miniature components and microstructures are increasingly in demand in the sector of electro-optics, automotive, biotechnology, aerospace and information-technology industries. A rational approach to mechanical micro machining is to develop ultra-precision machines with small footprints. In part 1 of this two-part paper, the-state-of-the-art of ultra-precision machines with micro-machining capability is critically reviewed. The design considerations and specifications of a five-axis ultra-precision micro-milling machine—UltraMill—are discussed. Three prioritised design issues: motion accuracy, dynamic stiffness and thermal stability, formulate the holistic design approach for UltraMill. This approach has been applied to the development of key machine components and their integration so as to achieve high accuracy and nanometer surface finish

Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation

The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this work, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this study, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.Comment: Accepted to be published by IEEE Trans. on Intelligent Vehicles, 22 Jan 201