Georg Jacobs

Model predictive control of a wind turbine modelled in Simpack

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbines components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to SlMPACK. This modeling approach allows to investigate the nonlinear behavior of wind loads and nonlinear drive train dynamics. Thereby the MPCs impact on specific loads and effects not covered by standard simulation tools can be assessed and investigated. Keywords. wind turbine simulation, model predictive control, multi body simulation, MIMO, load alleviation

Testing nacelles of wind turbines with a hardware in the loop test bench

Testing of wind energy converters (WEC) at ground level in contrast to an in-field setup has increased in the last years. As it is an approach which is fundamentally different to in field-testing, it requires significant modifications of the measurement environment and the layout of the sensor system. To increase the reliability of WECs, a detailed investigation of the status of various electrical and mechanical values is necessary because good condition monitoring guarantees a well-controlled state of the turbine in the desired point of operation. This leads to an appropriate maintenance strategy that enhances the lifetime of the WEC. Crucial physical values can be identified easier at ground level testing than with an in-field setup. This article addresses the realization of Hardware in the Loop (HIL) concepts on signal and power level for the use in WEC nacelle testing. Moreover, the functionality of the 1 MW demonstrator test bench operating in HIL mode with a DUT controlled by the original nacelle controller is shown.

Development of a 4 MW full-size wind-turbine test bench

The in-field validation of wind turbines behavior is very time consuming and cost intensive, especially when fault ride-through (FRT) tests are conducted. Full-size wind-turbine test benches allow a realistic operation of wind turbines in an artificial environment. Due to the independency of wind and grid conditions, the cost and duration of the test program and certification can be reduced. This paper presents the development of 4 MW full-size wind-turbine test bench following a multi-physics hardware in-the-loop (HiL) concept. With the currently installed test bench setup, a synchronization of the device-under-test converters is possible. Through the measurement results of the test programs conducted on the test bench, the capability of the test bench in replicating the field conditions is demonstrated. In addition, a time consuming efficiency measurement can be performed with the reduced duration on the test bench. This shows another main benefit of the test bench compared to the conventional test method for wind turbines.

Hybrid NVH Simulation for Electrical Vehicles II - Structural Model

Introduction The FVA research project No. 682 provides a fast, modifiable simulation tool starting with a model for the electrical drive train and resulting in a binaural auralization in the car cabin. The tool enables developers to freely change the properties of the electric drive components and listen to the resulting acoustics within a short time span. For this purpose, a fully-coupled drive train simulation model has been developed for the calculation of surface velocities and forces. The goal is a valid high frequency (<5000Hz) Multi-Body-Simulation (MBS) model of the drive train which fulfills the requirements of the entire simulation method for a binaural auralization. Therefore, a possibility for implementation of electromagnetic forces is needed and the exporting of surface velocities and forces at specific points is necessary.

CFD simulation of elastohydrodynamic lubrication problems with reduced order models for fluid-structure interaction

Abstract Recently, simulations of elastohydrodynamic lubrication (EHL) problems based on a coupled solution of the Navier–Stokes equations and solid mechanics have been presented. Compared to classical approaches in EHL, however, the simulation time is significantly higher. In this work, the elastic solids are represented by reduced finite element (FE) models in order to decrease the calculation time while keeping the possibility to simulate complex geometries and materials. To eliminate the necessity of matching meshes at the fluid–solid interface, an interpolation method based on radial basis functions is applied to an EHL line contact. By using this energy-conserving interpolation, the number of solid interface points is reduced by a factor of four compared to the fluid interface points with approximately identical pressure and film thickness profiles. Hence, the memory size of the FE matrices can be reduced by more than 90%, leading to an efficient deformation calculation even for complex solids.

Application of CPS Within Wind Energy—Current Implementation and Future Potential

Wind energy is a growing market and features high development potential on many levels in the future. In order to make use of the manifold potential, available data of wind turbines needs to be analyzed and advanced measuring technologies and communication networks have to be implemented. Hence, application of Cyber Physical Systems (CPS) can be a powerful approach to further develop the wind energy sector. Currently applied forms of CPS in wind energy are CMS or SCADA systems. However, these systems are not sufficient enough as a more extensive data analysis and communication network is required. Therefore, a future CPS in wind energy is presented in this article, which is the proposed next step in wind energy development. This advanced CPS is capable to reduce O&M costs and considers all relevant parameters of the power grid in order to optimize the operation and increase the efficiency of wind turbines and farms.

Cyber-Physical Systems for Agricultural and Construction Machinery—Current Applications and Future Potential

This chapter presents an overview of the current applications and future potentials of Cyber-Physical Systems (CPS) in the agricultural and construction machinery sectors. The different challenges in both sectors are explained and a typical CPS structure for mobile machines is described. This is followed by a categorization of data in mobile machinery and a description of the future impact on communication strategies. Six key technologies enabling the creation of CPS are defined and discussed in the context of agricultural and construction machinery. In addition, ten key algorithms are presented, which enable the definition of strategies by smartly and efficiently processing and combining data. At the end of this chapter, two typical processes, a street construction process and a crop growth cycle are analyzed in detail. In this context, the applications of the key technologies and key algorithms are exemplified.

Noise, vibration and harshness validation methodology for complex elastic multibody simulation models: With application to an electrified drive train

Numerical models for vibro-acoustic analyses of complex mechanical systems are becoming more and more popular, in particular in the field of virtual product development. Therefore, reliable, comprehensive, and validated modeling methodologies remain crucial. However, system characteristics such as elasticities of the drive train components and nonlinear characteristics can lead to complex, and costly numerical models with a huge number of degrees of freedom. This may raise not only the need for novel and reasonable modeling strategies, but also exacerbates validation process, due to the wide scope in terms of operating conditions. In practice, structure-borne noise signals, for example, from accelerometers, are often used for the validation of mechanical systems. By choice of a sufficient number of measurement points, the interpretation becomes more complex. A lot of vibration response curves then need to be compared and interpreted over a wide operating range. In general, the interpretation focuses on deviations in quality and quantity. In this paper, to overcome these mentioned challenges, a validation methodology is proposed allowing a fast and transparent check of a number of captured signals. Therefore, it is shown how the original information can be reduced in a meaningful manner, making it possible to run a fast and accurate validation. The method is demonstrated on a real application with high mechanical complexity and it is shown that the chosen parameters are reliable.

Robustness Test for Wind Turbine Gearbox Bearings

This paper introduces an innovative approach for the creation of the robustness test against specific failures of the planetary and HSS bearings (e.g. classical fatigue, smearing, micro-pitting, and lip fractures) in the wind turbine gearboxes. The introduced Bearing Robustness Test (BRT) considers the system-dependent characteristics (e.g. drive train design, interaction between components, assembly process, lubricant aging) and real dynamic load conditions, frequencies and sequence. The creation of the BRT is based on field and simulation data. The core element is the simulative approach for the determination of the relation between external wind and grid loads on the one side and local loads of the bearing on the other side. BRT aims the mapping of the most critical, but real, field load situations in the bearing test rig. By means of the BRT it is possible to evaluate the robustness of bearing against specific field conditions in the early stage of the product cycle and consequently to enhance the quality and to reduce the failure rate of the bearing. 1. Motivation and Objectives The cost-efficiency of the wind turbines is reduced by the frequent failures of the main gearboxes. The main gearbox is responsible for nearly 60 % of the downtime of the wind turbine, see Figure 1. This fact is caused by a fluctuating and dynamic wind and grid loads, dynamic interaction between drive train components as well as the demand for high power density of the gearbox components [1]. Therefore, the rolling contact bearings are the most critical component of the main gearbox. They contribute to over 67 % of main gearbox failures according to the current research, see Figure 1. The planetary and high-speed shaft (HSS) bearings failures cause high reparation, replacement and service costs [3]. Bearing testing methods within the product development process could contribute to more reliable and robust gearbox bearings and thereby increase the availability of the wind turbines. Nowadays, the existing testing methods cannot completely simulate the real elastic surroundings and reproduce the complex load situation on the bearing as well as the complex interaction between the gearbox components. Consequently, it is difficult to reproduce specific wind turbine bearing failures in a realistic way [4]. To solve this challenge, a diversified consortium of a complete product value chain (bearing, gearbox and wind turbine manufacturer)1 under the lead management of Chair for Wind Power Drives (CWD) got together to develop a new bearing test rig designs (a planetary 1 Schaeffler, SKF, Timken, NTN, Siemens Winergy, ZF Wind Power, Eickhoff, Vestas, Nordex, Senvion Figure 1. Causes for wind turbine downtime. 3% 3% 8% 2% 25%

Friction as a major uncertainty factor on torque measurement in wind turbine test benches

Most of the existing multi-MW nacelle test benches (NTB) measure the MNm torque before load application system (LAS) to reduce the cross-talk effect of the multi-component forces and bending moments on torque measurement. This means that the friction torque of the LAS reduces the applied torque and consequently directly determines the input torque on the device under test (DUT). Therefore, the knowledge of the friction torque is necessary for the precise experimental investigations (e.g. efficiency measurement). At the beginning of this paper, a Computational Fluid Dynamics (CFD) simulation method for the determination of the friction torque of the LAS, which is suspended by hydrostatical plain bearings, is introduced. Subsequently, this method is validated with experimental results. Afterwards the friction torque of the LAS is quantified under different operation conditions (e.g. variation of rotational speed, multi-component load and temperature). Finally, the influence of the quantified friction torque on the uncertainty of the MNm measurement is compiled.