UNIDAD 3. Procesos de cambio de forma
3.2 Formado Mecánico(Prensado, Estirado, Cizallado, Doblado)
7.6.1 Overview of hardware
Figure 7.14 shows the drive train test bed developed for tidal stream turbine simulations. The test bed motor can be controlled to replicate the turbine rotor input to the drive train. In this case the motor is directly coupled to a generator for power extraction thereby effectively enabling the simulation of both a direct-drive and geared tidal stream turbine equipped with a permanent magnet synchronous generator. To allow for flexibility the two rotating machines are of the servo type with on board encoders measuring the rotor velocity and position for feedback control. The machines are Bosch Rexroth IndraDyn MSK 050Cs and are synchronous permanent magnet machines rated with a maximum velocity of 4300 RPM and a maximum torque of 9 Nm. A proprietary flexible coupling was used to connect the machine’s drive shafts.
184 The motor drives setup is shown in Figure 7.15. The drives used were the Indradrive Cs which were set-up as master and slave utilising the SERCOS III communication protocol. The master drive was then connected via Modbus TCP/IP to a National Instruments Compact RIO. The TST model and maximum power point tracking control loops were implemented using the Real-Time operating system in the Compact RIO and the rotor and generator commands were sent to the motor drives via the Modbus link. The motor drives utilised close-loop vector oriented control to implement the commands sent from the Compact RIO. For the simulations undertaken the speed of the turbine was set by commanding the rotational velocity of the generator which was achieved via load output regulation. The motor was control to replicate torque commands output form the parametric model given the current parameters and simulation data.
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Figure 7.15: Motor drives and Compact RIO arranged in the drive cabinet.
Figure 7.16 shows a schematic of the test rig indicating the interaction between each of the hardware elements. The figure also shows the flow of information highlighting the use of measured data for recursive simulation calculations and the storing of data for further analysis. The numbers circled within each of the elements relate the elements of the overall simulation schematic presented in Figure 7.1 to the hardware schematic in Figure 7.16. Specifically the calculation of each numbered element is undertaken via the hardware labelled with the corresponding number in Figure 7.16.
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Figure 7.16: Schematic of the interacting hardware elements and the distribution of functionalities across the hardware platforms.
7.6.2 Vector Oriented Control of PMSM.
The PMSM utilised for the test rig setup were setup to implement vector oriented control (VOC). In the case of the motor the goal of the VOC was to operate the motor in a similar fashion to a TST via the application of appropriate torsional loads which are calculated via the outlined rotor model. The goal of the VOC for the generator is to control the generator load in order to realise optimal TSR control.
The idea of vector oriented control has been previously utilised for motor and generator control. Its use in relation to tidal stream turbine control has been reported (Liang and Whitby, 2011). The process related to applying this to wind turbine control has also been reported (Anaya-Lara, 2009). In the case of a PMSG, this is done by noting that under normal operation the id current in Equation 3.8 is weakening the magnetic
flux producing the generator feedback torque and can therefore be set to zero, this gives:
𝜏𝑒 =
2
187 For a set-point torque required to accelerate or decelerate the turbine velocity to the required optimal rotational velocity the reference direct and quadrature currents are given by: 𝑖𝑑𝑟𝑒𝑓 = 0 (7.12) 𝑖𝑞𝑟𝑒𝑓 = 3 2 𝑇𝑠𝑝 𝑝 ∙ 𝜑 (7.13)
The required voltage in the direct and quadrature axis can be found be re-arranging (7.13) and (7.14).
𝑣𝑑𝑟𝑒𝑓= 𝑅𝑖𝑑+ 𝜔𝑟𝐿𝑞𝑖𝑞 (7.14)
𝑣𝑞𝑟𝑒𝑓 = −𝑅𝑖𝑑𝑞− 𝜔𝑟𝐿𝑑𝑖𝑑 + 𝜔𝑟 𝜑 (7.15)
The voltage reference signal is then input into a PWM module which generates the switching sequence for the IGBT to regulate the phase voltages of the generator to give the required generator feedback torque which will result in the set-point λ value required for peak power extraction. The VOC control scheme was implemented in the drive systems of the PMSMs and was developed by Bosch Rexroth as a standard control system for the machines utilized. A schematic of the control process implemented via three cascaded control loops is shown in Figure 7.17 (Bosch Rexroth AG, 2011).
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Figure 7.17: Control structure implemented in the Bosch Rexroth drive utilising VOC for torque (current), velocity and position control of the PMSM (Bosch Rexroth AG, 2011).
7.6.3 Software Implementations
In order to implement the parametric simulation method constructed by the author various software elements had to be incorporated. Specifically the author wrote software routines for each of the platforms highlighted in Figure 7.16. The PC and Compact RIO ran software routines constructed in LabVIEW which were constructed as a single software project distributed between the Windows operating system (Host PC) and the NI Real-Time operating system (Compact RIO). The IndraDrive Cs systems ran software routines which were implemented via structured text. The majority of the software implemented was engineered to allow data capture and sharing between the various platforms as required. Furthermore software was implemented to allow for user interface functionalities and for the input of test settings, fluid velocity time-series and
189 parameter surfaces. The main element of the software was the parametric model implementation, presented below.
The model calculation is made as highlighted on Figure 7.18. The three main aspects of the calculations are using the motor measurements and fluid velocity value for the given time step to calculate the current operating tip-speed ratio. In the same stage the tip-speed ratio is used to interpolate the turbine non-dimensional torque curve and parameter surfaces to obtain the torque coefficient, Cθ, the amplitude parameters, ai, and lastly the phase angle parameters pi. In the next step the parameters set outlined, rig measurements and the fluid velocity value for the time step are used to calculate the turbine rotor torque. The calculation is made using the formulation outline in Section 7.4 and as discussed returns a realisation of the process for the given rotor position and simulation settings. A new ‘realisation’ is returned each time step and time steps corresponding to equal rotor displacements and fluid velocity settings will not necessarily return equal torque values. However, the process mean for a given displacement and fluid velocity value will be equal to the value calculated via equation 7.9 with the random variable Z set to zero.
The last step calculates the set point rotational velocity for either optimal TSR control or for fixed velocity control. The generator velocity and the motor torque commands are output as scaled voltages, in the range 0 V - 10 V, which are input to the built-in analogue inputs on the IndraDrives Cs. The new measurements from the motor and generator are acquired and used to update the turbine state. The updated variables or turbine state is then used for the next execution of the calculation loop.
In order to undertake the first iteration of the model calculations outlined above the first fluid velocity value must be read and the generator set to the required velocity. This is done during a 30 second period allowing the rig to reach the required velocity and to successfully send data to the Compact RIO. At the end of the 30 second period the final
190 measurements of motor and generator parameters are input to the model for the first iteration.
Prior to the simulation start and run-in period the software is controlled via user input. Under this state the user is able to select the fault states to be simulated and if there is to be a change in turbine characteristics during the simulations. In order to set the turbine characteristics the user loads files in to the software containing the turbine non- dimensional torque curve, amplitude surface and phase surface. Furthermore the user can upload a fluid velocity time series generated via the process outlined in Section 7.3 prior to simulation. Lastly, it is worthwhile noting that the author made efforts to create highly modular software whereby changes to the simulation approach can be easily achieved. Chapter 8 presents the results of a CM study made based on the outlined simulation approach. The simulations considered fixed speed and optimal TSR turbine operations and the impact of such turbine operation on the use of generator signals for rotor fault detection and diagnosis are further investigated.
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Figure 7.18: Screen shot of the LabVIEW code implementation of the parametric rotor model and turbine control processes discussed throughout this chapter.
Ge t flui d ve locit y , TS R and P ara mete rs for ti me ste p C alcula te r otor torque uti li sing the pa ra met ric model S tate upda te for ne x t ca lcula ti on
192