A Self-Sensing Method for Electromagnetic Actuators with Hysteresis Compensation

Self-Sensing techniques are a commonly used approach for electromagnetic actuators since they allow the removal of position sensors. Thus, costs, space requirements, and system complexity of actuation systems can be reduced. A widely used parameter for self-sensing is the position-dependent incremental inductance. Nevertheless, this parameter is strongly affected by electromagnetic hysteresis, which reduces the performance of self-sensing. This work focuses on the design of a hysteresis-compensated self-sensing algorithm with low computational effort. In particular, the Integrator-Based Direct Inductance Measurement (IDIM) technique is used for the resource-efficient estimation of the incremental inductance. Since the incremental inductance exhibits a hysteresis with butterfly characteristics, it first needs to be transformed into a B-H curve-like hysteresis. Then, a modified Prandtl–Ishlinskii (MPI) approach is used for modeling this hysteretic behavior. By using a lumped magnetic circuit model, the hysteresis of the iron core can be separated from the air gap, thus allowing a hysteresis-compensated estimation of the position. Experimental studies performed on an industrial switching actuator show a significant decrease in the estimation error when the hysteresis model is considered. The chosen MPI model has a low model order and therefore allows a computationally lightweight implementation. Therefore, it is proven that the presented approach increases the accuracy of self-sensing on electromagnetic actuators with remarkable hysteresis while offering low computational effort which is an important aspect for the implementation of the technique in cost-critical applications

Development of Magnetic Shape Memory Alloy Actuators for a Swashplateless Helicopter Rotor

Actuator concepts utilizing NiMnGa, ferromagnetic shape memory alloy are investigated for potential use on a smart rotor for trailing edge flap actuation. With their high energy density, large dynamic stroke, and wide operating bandwidth, ferromagnetic shape memory alloys (FSMA) like NiMnGa, seem like attractive candidates for smart rotor actuators, potentially able to fulfill the requirements for both primary rotor control and vibration suppression. However, because of the recent discovery of the material, current experimental data and analytical tools are limited. To rectify these shortcomings, an extensive set of detailed experiments were conducted on samples of NiMnGa to characterize the response of the alloy for a wide variety of mechanical and magnetic loading conditions. Measurements of the material performance parameters such as power density, damping properties, magneto-mechanical coupling, and transduction efficiency were included. Once characterized, the experimental data were used to develop a series of analytical tools to predict the behavior of the material. A model, developed in parallel to thermal shape memory alloy models is proposed to predict the quasi-static stress-strain behavior. A simple, low frequency, parameter based model was also developed to predict the alloy's dynamic strain response. A method for developing conceptual actuators utilizing NiMnGa as the actuation element was proposed. This approach incorporates experimental data into a process that down-selects a series of possible actuator configurations to obtain a single configuration optimized for volumetric and weight considerations. The proposed actuator was designed to deliver 2 mm of stroke and 60 N of force at an actuation frequency of 50 Hz. However, to generate the 1.0 T magnetic field, the actuator mass was determined to be 2.8 kg and required a minimum of 320 Watts of power for operation. The mass of the NiMnGa element was only 18.3 g. It was concluded that although the NiMnGa alloy was capable of meeting the trailing edge flap actuation requirements, the material is not suitable in its present form for this application because of weight and power consumption issues. The magnetic field requirements must be reduced to improve the utility of the material for rotorcraft applications

A finite element approach for the implementation of magnetostrictive material terfenol-D in automotive CNG fuel injection actuation

Magnetostriction is the deformation that spontaneously occurs in ferromagnetic materials when an external magnetic field is applied. In applications broadly defined for actuation, magnetostrictive material Terfenol-D possesses intrinsic rapid response times while providing small and accurate displacements and high-energy efficiency, which are some of the essential parameters required for fast control of fuel injector valves for decreased engine emissions and lower fuel consumption compared with the traditional solenoid fuel injection system. A prototype CNG fuel injector assembly was designed, which primarily included magnetostrictive material Terfenol-D as the actuator material, 1020 Steel having soft magnetic properties as the injector housing material, AWG copper wire as the coil material and 316 Stainless Steel having non-magnetic properties as the plunger material. A 2D cross-sectional geometry including the injector housing, coil, Terfenol-D shaft, and plunger, was modeled in both Finite Element Method Magnetics (FEMM) and ANSYS for 2D axisymmetric magnetic simulation. The magnetic simulations were performed in order to determine the coil-circuit parameters and the magnetic field strength to achieve the required magnetostrictive strain, and consequently, the injector needle lift. The FEMM magnetic simulations were carried out with four different types of AWG coil wires and four different injector coil thicknesses in order to evaluate the relationship between the different coil types and thicknesses against the achieved strain or injector lift. Eventually, the optimized parameter obtained from FEMM results analysis was verified against ANSYS electromagnetic simulation. Subsequently, a three dimensional replica of the CNG flow conduit was modelled in GAMBIT with the resultant injector lift. The meshed conduit was then simulated in FLUENT using the 3D time independent segregated solver with standard k-ε, realizable k-ε and RSM turbulent models to predict the mass flow rate of CNG to be injected. Eventually, the simulated flow rates were verified against mathematically derived static flow rate required for a standard automotive fuel injector considering standard horsepower, BSFC and injector duty cycle

A Simulation Method for Design and Development of Magnetic Shape Memory Actuators

The systems/products and their design processes have become more and more complicated due to the fact that their requirements in terms of function, durability, reliability and energy efficiency have been increased significantly and that their leading time has to be short and their materials cost has to be low. To meet these requirements, individual parts and subsystems have to offer increased functionality and efficiency themselves. It has been found that smart materials, such as piezo ceramics or various shape memory alloys as well as less known dielectric elastomers or magnetic shape memory alloys, offer ideal preconditions to fulfil such requirements. Among the various shape memory alloys, the Magnetic Shape Memory (MSM) alloy is a kind of smart material that can elongate and contract in a magnetic field. Based on the MSM alloy a new type of smart electromagnetic actuators have been designed and developed. This kind of actuator exhibits the features above. Typically, the MSM material is a monocrystalline Ni-Mn-Ga alloy, which has the ability to change its size or shape very fast and many million times repeatedly. State-of-the-art alloys are able to achieve a magnetic field induced strain of up to 12%. The magneto-mechanical characteristic of MSM alloys is being constantly improved. However, as far as the author is aware, there are no efficient and commercially available tools for engineers to design MSM-based actuators. To achieve this, simulation tools for design are indispensable. This thesis is dedicated to this task. In this PhD thesis, new design and simulation techniques for MSM-based actuators have been studied. In particular, three simulation methods have been proposed. These three methods extend standard magneto-static FEM simulation techniques by taking into account the magneto-mechanical coupling and the magnetic anisotropy of the MSM materials. They differ in terms of the necessary a priori alloy characterisation (i.e., measurement effort), computational complexity and consequent computing time. The magneto-mechanical characteristics of the MSM material are a necessary and fundamental ingredient for this type of simulation. However, the characterisation of the MSM materials is a very challenging task and requires specific modifications to standard measurement approaches. So, in this thesis, some specific measurement methods of the magneto-mechanical characteristics of the MSM materials have been proposed, designed and developed. It is described how existing measurement instruments can be modified to measure the unique magneto-mechanical characteristics of MSM, so they are applicable and with practical values. Various tests have been carried out to validate the new methods and the necessary characterisations of the properties of MSM materials have been performed, such as the measurement of the permeability of MSM under a defined stress during elongation. The new measurement results have been analysed and the findings have been used to design and develop the simulation methods. The three simulation methods can be used to predict and optimise the current-elongation behaviour of an MSM element under the load of a mechanical stress while excited by a magnetic field. Extensive experiments have been carried out to validate these three simulation methods. The results show that the three methods are relatively simple but, at the same time, very effective means to model, predict and optimise the properties of an MSM actuator using finite element tools. In addition, the experiment results have also shown that the simulation methods can be used to gain some deep insights into the magneto-mechanical interaction between the MSM element and the electromagnetic actuator. In this thesis an evolutionary algorithm which works together with the simulation methods has been developed to achieve individual optimised solutions in very short times. In summary, from the experiment results, it has been found that the measurements and simulation methods proposed and developed in this thesis; enable designers to perform simulations for a high-quality actuator design based on the magneto-mechanical properties of MSM alloys. This is the first time that a MSM can be characterised for simulation purposes in a fast and precise way to predict MSM and electromagnetic actuator interactions and identify and optimise the design parameters of such actuators. However, these simulation methods are strongly dependent on the measurement of the magneto-mechanical characteristics of magnetic shape memory alloys, whose precision can be further improved. To reach commercial success as well higher precision in the simulation prediction, further achievements in the field of material science (e.g. smoothness of mechanical curves) are also necessary

Optimization of SI and CI engine control strategies via integrated simulation of combustion and turbocharging

2010 - 2011Combustion engines have been for a long time the most important prime mover for transportation globally. A combustion engine is simple in its nature; a mix of fuel and air is combusted, and work is produced in the operating cycle. The amount of combusted air and fuel controls the amount of work the engine produces. The engine work has to overcome friction and pumping losses, and a smaller engine has smaller losses and is therefore more efficient. Increasing engine efficiency in this way is commonly referred to as downsizing. Downsizing has an important disadvantage; a smaller engine cannot take in as much air and fuel as a larger one, and is therefore less powerful, which can lead to less customer acceptance. By increasing the charge density the smaller engine can be given the power of a larger engine, and regain customer acceptance. A number of charging systems can be used for automotive application, e.g. supercharging, pressure wave charging or turbocharging. Turbocharging has become the most commonly used charging system, since it is a reliable and robust system, that utilizes some of the energy in exhaust gas, otherwise lost to the surroundings. There are however some drawbacks and limits of a turbocharger. The compressor of a single stage turbo system is sized after the maximum engine power, which is tightly coupled to the maximum mass flow. The mass flow range of a compressor is limited, which imposes limits on the pressure build up for small mass flows and thereby engine torque at low engine speed. Further, a turbo needs to spin with high rotational speed to increase air density, and due to the turbo inertia it takes time to spin up the turbo. This means that the torque response of a turbocharged engine is slower than an equally powerful naturally aspirated engine, which also lead to less customer acceptance A two stage turbo system combines two different sized turbo units, where the low mass flow range of the smaller unit, means that pressure can be increased for smaller mass flows. Further, due to the smaller inertia of the smaller unit, it can be spun up faster and thereby speed up the torque response of the engine. The smaller unit can then be bypassed for larger mass flows, where instead the larger turbo unit is used to supply the charge density needed. In the dissertation, the value of engine system modeling has been discussed. It was shown how modeling in-cylinder processes and turbocharger can aid the development of the control strategies saving time and money efforts. All the developed models were experimentally validated and applied for optimization analysis or real-time control. Particularly the model based optimization of the engine control variables of an automotive turbocharged Diesel engine has been presented. The model structure is based on a hybrid approach, with a predictive multi-zone model for the simulation of in-cylinder processes (i.e. combustion and emissions formation) integrated with a control-oriented turbocharger model to predict intake/exhaust processes. Model accuracy was tested via comparison between measured and simulated in-cylinder pressure and engine exhaust temperature on a wide set of experimental data, measured at the test bench. Validation results exhibit a correlation index R2 equal to 0.995 and 0.996 for IMEP and exhaust temperature, respectively. The optimization analysis was aimed at minimizing NO emissions in four steady state engine operating conditions, selected among those of interest for the ECE/EUDC test driving cycle. Constraints were introduced to prevent from increase of soot emissions and low exhaust temperature which would have a negative impact on the efficiency of the after-treatment devices. The optimization results evidence a significant reduction of engine NO emissions by means of increased EGR rate and earlier main fuel injection. A model-based optimization was also applied for a CNG heavy-duty engine, equipped with turbocharger and EGR. The optimization analysis was addressed to design the set-points of engine control variables, following the implementation of an EGR system aimed at reducing the in-cylinder temperature and preventing from the thermal stress of engine components (i.e. head and valves). A co-simulation analysis was carried out by coupling a 1-D engine commercial code with a classical constrained optimization algorithm. The 1-D model accounts for intake and exhaust gas flow arrangement, comprehensive of EGR system and turbocharger, while an empirical formulation based on the classical Wiebe function was implemented to simulate the combustion process. An intensive identification analysis was performed to correlate Wiebe model parameters to engine operation and guarantee model accuracy and generalization even in case of high EGR rate. 1-D model and identification results were successfully validated against a wide set of experimental data, measured on the test bench. The results of the optimization analysis, aimed at minimizing fuel consumption while preventing from thermal stress, showed an increase of fuel economy up to 4.5% and a reduction of the thermal load below the imposed threshold, against five engine operating conditions selected among the most critical of the reference European Transient Cycle (ETC). Particularly, the effectiveness of the co-simulation analysis is evidenced in pursuing the conflicting goal of optimizing engine control while reducing the recourse to time consuming and expensive experiments at the test bed. This latter point is becoming more and more critical as the number of control variables is increasing with engine complexity. Both the presented optimization analyses evidenced the key-role of the turbocharger to face with energy and emissions issues. Particularly the impact of the turbocharger management via wastegate or VGT control was evidenced. Indeed, by acting on these components, the amount of exhaust gases evolving in the turbine can be managed thus regulating the supercharging degree and the boost pressure. This allows keeping the throttle valve fully open with significant decrease of pumping losses. The wastegate position is defined by a pneumatic actuator in which the pressure is regulated by a solenoid valve fed by a PWM signal. The drawback of this system is the dependence of the PWN signal, and afterwards of the performance, from the system supply voltage. During the thesis the development of a wastegate actuator model was carried out in order to compensate the actuator PWM signal to improve boost pressure control. The compressible flow equations were found to be sufficient to describe the actuator system mass flow and both discharge coefficient and static actuator chamber pressure were modeled using polynomials in PWM signal. Furthermore a simple friction model was implemented to simulate the actuator system. The boost pressure controller based on the developed compensator has shown to give limited undershoot and overshoot and is further able to reject the disturbance in supply voltage. The compensator was incorporated into a boost pressure controller and the complete control system has shown to reject system voltage variations and perform good boost pressure control in both simulations analyses and experimental tests on the engine test stand. Model simulations evidenced the need to ensure low enough vacuum pressure to enable fully closed and open actuator while a switch type controller was proved to be sufficient for vacuum tank pressure control. [edited by author]X n.s

DEVELOPMENT OF A SNUBBER TYPE MAGNETORHEOLOGICAL FLUID ELASTOMERIC LAG DAMPER FOR HELICOPTER STABILITY AUGMENTATION

Most advanced helicopter rotors are typically fitted with lag dampers, such as elastomeric or hybrid fluid-elastomeric (FE) lag dampers, which have lower parts counts, are lighter in weight, easier to maintain, and more reliable than conventional hydraulic dampers. However, the damping and stiffness properties of elastomeric and fluid elastomeric lag dampers are non-linear functions of lag/rev frequency, dynamic lag amplitude, and operating temperature. It has been shown that elastomeric damping and stiffness levels diminish markedly as amplitude of damper motion increases. Further, passive dampers tend to present severe damping losses as damper operating temperature increases either due to in-service self-heating or hot atmospheric conditions. Magnetorheological (MR) dampers have also been considered for application to helicopter rotor lag dampers to mitigate amplitude and frequency dependent damping behaviors. MR dampers present a controllable damping with little or no stiffness. Conventional MR dampers are similar in configuration to linear stroke hydraulic type dampers, which are heavier, occupy a larger space envelope, and are unidirectional. Hydraulic type dampers require dynamic seal to prevent leakage, and consequently, frequent inspections and maintenance are necessary to ensure the reliability of these dampers. Thus, to evaluate the potential of combining the simplicity and reliability of FE and smart MR technologies in augmenting helicopter lag mode stability, an adaptive magnetorheological fluid-elastomeric (MRFE) lag damper is developed in this thesis as a retrofit to an actual fluid-elastomeric (FE) lag damper. Consistent with the loading condition of a helicopter rotor system, single frequency (lag/rev) and dual frequency (lag/rev at 1/rev) sinusoidal loading were applied to the MRFE damper at varying temperature conditions. The complex modulus method was employed to linearly characterize and compare the performance of the MRFE damper with the baseline FE damper performance. Based on experimental measurements, it is shown in the research that at all test temperatures, a significant damping control range, extending beyond the baseline FE damper, can be provided by the MRFE damper with the application of varying magnetic fields. This controllable damping range can be programmed to potentially provide the required damping augmentation as a function of different flight conditions. The added benefits of employing smart MR fluids in MRFE lag dampers are to produce adequate damping at critical flight conditions while concurrently reducing periodic hub loads at other flight conditions and to compensate damping losses associated with temperature. The other main objective of the present research is to develop and formulate a comprehensive analytical model that can accurately describe the non-linear hysteretic behavior that is demonstrated by the MRFE lag damper. Thus, a hydromechanical model, which can delineate the physical flow motion of the system and accurately describe the non-linear hysteretic behavior of the MRFE damper is proposed. The hydromechanical model explored in this study is a design-based model which describes the damper system with a series of lumped hydraulic, mechanical and magnetorheological components. The model employs physical parameters such as inertia, damping, yield force and compliances that are dependent on damper geometry and material properties of components and which can potentially be approximated a priori. Further, temperature variation will mainly cause material properties to change. Once model parameters have been established, the model is shown to simulate accurately the measured hysteretic force-displacement history under single and dual frequency excitations, and varying temperatures