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Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

Model Fidelity Study of Dynamic 

Transient Loads in a Wind 

Turbine Gearbox

Preprint

Y. Guo and J. Keller

National Renewable Energy Laboratory

T. Moan and Y. Xing

Centre for Ships and Ocean Structures (CeSOS) - 

Norwegian University of Science and Technology (NTNU)

To be presented at the 2013 WINDPOWER Conference

Chicago, Illinois

May 5 – 8, 2013

Conference Paper

NREL/CP-5000-58414

April 2013
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1 *

yihan.xing@ntnu.no

Model Fidelity Study of Dynamic Transient Loads in a Wind Turbine gearbox

Yihan Xing* 

CeSOS, NTNU

Trondheim, Norway

Yi Guo

NWTC, NREL

Colorado, USA

Jonathan Keller

NWTC, NREL

Colorado, USA

Torgeir Moan

CeSOS, NTNU

Trondheim, Norway

Abstract

Transient events cause high loads in wind turbine drivetrain components, so measuring and calculating these loads can 

improve confidence in drivetrain design. This paper studies the response of the Gearbox Reliability Collaborative 750-kW 

wind turbine gearbox during transient events using a combined experimental and modelling approach. The transient 

events include emergency shutdowns and start-ups measured during a field testing period in 2009. The drivetrain model is 

established in the multibody simulation tool Simpack. A study of modelling fidelity required for accurate load prediction 

was performed and results were compared against measured loads. A high-fidelity model that includes shaft and housing 

flexibility and accurate bearing stiffnesses is important for the higher-speed stage bearing loads. Including the flexibility 

of main shaft and planet carrier is important to simulate shutdown events compared to start-ups because main shaft 

bending loads are much higher in shutdown events than those during startups.

Keywords: wind turbine gearbox, field-test measurements, multibody method, transient events

1. Introduction

The gearbox is a crucial and expensive component of the wind turbine and has experienced higher-than-expected failure

rates. De Vries [1] suggested that there is a lack of insight in transient drivetrain behaviour that occurs during control 

actions or generator faults. These transients can lead to unexpected torque reversals and generator faults that can be 

harmful to drivetrain components. Understanding the effects of transient events on wind turbine gearboxes is important, 

and this paper examines the modelling of the gearbox under such events.

In previous work, the authors have performed various modelling studies of the National Renewable Energy Laboratory 

(NREL) Gearbox Reliability Collaborative’s (GRC) gearbox [2]. This included the study of the required model fidelity 

with comparisons to dynamometer test measurements in LaCava el al. [3, 4] and detailed study of the modelling of the 

planet carrier in Xing et al. [5]. Other examples of work in gearbox modelling include LaCava et al. [6, 7], Oyague el al. 

[8-11], Peeters et al. [12-14], Helsen et al. [15-18], Xing et al. [19, 20] and Guo et al. [21, 22]. The results from the 

previous work have been positive, however, the validated drivetrain model for test stand conditions might not perform as 

well for field conditions. Furthermore, these previous works focused almost solely on measurements in the low-speed 

planetary stage. This paper takes the previous work a step further by using comparisons against actual field-test 

measurements and additional gearbox stages. The field-test measurements provide a unique opportunity to further validate 

the multibody drivetrain models against field conditions. It is also important to compare the models against transient field

measurements as the original models that were validated using steady-state dynamometer tests might not work as well for 

the transient-load cases. The work performed in this paper fills this gap in model validation. 

This work is presented in three parts. First, the multibody drivetrain model is compared against the measurements from 

two transient load events. The variables compared are the planet bearing radial forces during a normal start-up and an 

emergency shutdown. Second, a more detailed model fidelity study of the multibody drivetrain model involving response 

variables from all the stages is performed using the measurements as inputs. Finally, the effect of individual flexible 

bodies on the calculated responses is also investigated. 
2 

2. Test Article

The test article used for this study was the wind turbine (WT) from the National Renewable Energy Laboratory’s (NREL) 

Gearbox Reliability Collaborative (GRC) project [2]. The GRC WT is a 750-kW, stall-regulated, dual-speed, three-bladed 

upwind machine. The GRC gearbox has one planetary and two parallel stages and uses the three-point support system. 

The input and output shafts are not co-axial. Its topology is similar to those of the larger, conventional, variable-speed, 

multimegawatt gearboxes seen today. The GRC drivetrain and gearbox are shown in Figure 1. The steady-state system 

characteristics of the GRC WT are presented in Figure 2. The WT is parked above the cut-out wind speed of 25 m/s. The 

gearbox topology and naming convention for each individual bearing is presented in Figure 3. The INP-A (spherical roller 

bearing) represents the main shaft bearing; PLC-A and PLC-B (full complement cylindrical roller bearings) represent the 

planet carrier bearings; and PL-A and PL-B (cylindrical roller bearings) represent the planet gear bearings. LS-SH-A, LSSH-B and LS-SH-C, IMS-SH-A, IMS-SH-B and IMS-SH-C and HS-SH-A, HS-SH-B and HS-SH-C represent the low-, 

intermediate-, and high-speed stage bearings, respectively. The upwind bearings in these stages are cylindrical roller 

bearings, while the downwind bearings are tapered roller bearings. The B and C bearings, therefore, carry the axial forces 

acting on the shafts in this bearing setup. A floating sun system should allow for better load sharing between the three 

planet gears in the low-speed planetary stage.

Figure 1: The GRC drivetrain and gearbox 

Figure 2: The GRC WT steady-state system characteristics calculated by FAST 
3 

Figure 3: The GRC gearbox topology 

2.1. Measurement Setup

The GRC project instrumented two gearboxes for dynamometer and field testing. Internal measurements include gear 

tooth loads, component deflections and misalignments, and planet bearing loads. The full description of instrumentation is 

detailed in Link et al. [2]. The instrumentation used to measure the planet bearing loads is shown in Figure 4. For each 

planet bearing, three axial slots were machined into the inner diameter of the inner ring and instrumented with strain and 

temperature gauges. Two of the slots were located at different circumferential locations in the bearing load zone for each 

planet, and the third slot for every bearing was oriented 90° from the sun-planet axis (referred to here as top dead center or 

TDC). Two gauge sets in each TDC slot and two bearings on each planet provided an axial distribution of four radial 

loads along each planet pin.

Figure 4: Strain gauges mounted on the planet bearing inner races from Link at al. [2] 
4 

3. Multibody Simulation of the Drivetrain

The drivetrain is modelled using the multipurpose multibody simulation software, SIMPACK. Each component of the 

drivetrain is modelled as a rigid or flexible body. The components are interconnected using joints, force elements, and 

constraints. The shafts, planet carrier, gearbox housing, and bedplate can be modelled as flexible bodies. The flexible 

bodies are modelled using condensed finite element (FE) models imported from Abaqus. These flexible bodies are derived 

via a two-step process. First, a condensation of the FE model is performed to yield reduced mass and stiffness matrices. 

Second, modal analysis is performed on the reduced matrices to yield the eigenmodes, and a subset of these modes is 

chosen for the final flexible body. This final flexible body is used in SIMPACK. In the planet carrier model, a total of nine 

interface nodes for the main shaft, pin interfaces, and the bearing interfaces are retained. These nodes are also coupled to 

their respective regions of nodes. A rigid coupling constraint for the main-shaft interface and flexible coupling constraints 

for the remaining interfaces are found to be ideal in Xing et al. [5]. The gear wheels are modelled using rigid bodies with 

tooth compliance. Tooth compliance is modelled using SIMPACK’s gear pair element, FE225, which models gear contact 

as a series of discrete springs and dampers. The gear stiffness is calculated in accordance with ISO 6336-1 [23]. This 

stiffness parameter depends on the location of the contact point and the gear geometry. The forces and torques acting on 

each individual gear are then calculated as a function of the gear stiffness and the penetration depth at the gear teeth. The 

FE225 element also considers normal damping, coulomb friction, backlash, and micro-geometry. The bearings are 

modelled using force elements that use stiffness matrices to represent the bearing stiffness.

No one single model is perfect for all types of simulations; therefore, this paper will also study the level of model fidelity 

required to reproduce the various field-test measurements. The level of model fidelity depends on the load conditions 

imposed on the model and the level of detail expected in the results. In Xing et al. [5], only the planetary stage was 

modelled as the main focus was a very detailed model of the planet carrier. On the other hand, in the drivetrain study of a 

floating spar-type wind turbine [19, 20], a drivetrain model that consists of six DOF gearwheels, bearing compliances, and 

flexible shafts were found to be sufficient for reasonable accuracy in the statistical responses in the drivetrain. Therefore, 

this level of model fidelity was chosen for that work. Figure 5 shows the SIMPACK model topology for the entire 

drivetrain used in this paper. The application of the main-shaft loads and generator speed into the multibody drivetrain 

model is illustrated in Figure 6. The main-shaft loads and generator speed are obtained from the measurements in this 

paper.
5 

Figure 5: SIMPACK model topology of the entire drivetrain. DOF stands for degree of freedom.
6 

Figure 6: Application of the main-shaft loads and generator speed into the multibody drivetrain model. The torque arms 

and housing casings are not shown.

4. Model and Experiment Comparison

Some field-test measurements are presented in Figure 7 and Figure 8. In these figures, LSS_SPD denotes the main-shaft 

speed, LSS_TRQ denotes the main-shaft torque, and PL1_A and PL1_B denote the radial loads for the upwind and 

downwind planet gear bearings, respectively. These load cases are emergency-shutdown and start-up events. As observed, 

these two events caused large torque loads on the main shaft and thus large internal drivetrain loads.

Previous comparisons to the dynamometer tests focused on measurements from the low-speed planetary stage, such as the 

planet bearing loads, planet gear deflections, sun gear orbit, and planet carrier rim deflection. In this paper, more emphasis 

was placed on the responses in the higher-speed stages. This is because the loads for some of the transient events, such as 

emergency-brake and start-up, are applied at the generator-side of the gearbox. This means that the higher-speed stages 

can experience large loads, and attention was given to accurately predict these loads in the multibody model.

Unfortunately, only the planet bearing radial forces were available; measurements from the higher-speed stages were not 

available. The field-test measurements were sampled at 10 Hz, and similarly, the computational results were also sampled 

at 10 Hz for comparison purposes. Note that using a lower sampling frequency will cause some local maximum responses 

to go undetected.

Comparisons of the measured and predicted planet bearing forces for both the start-up and emergency-shutdown events 

are presented in Figure 9. The computational results were calculated using the GB04 model, which is a high-fidelity 

model described in Section 5.1. As seen in Figure 9, the GB04 model with 40 elastic modes for each flexible body can 

reproduce the planet bearing forces well. The maximum forces calculated are within 3.2% and 2.0% of the measured 

values for the PL1-A bearing radial forces in the emergency-brake and start-up events, respectively. This model was used 

as the ‘correct’ model to provide responses for comparison in the entire drivetrain for the rest of this paper. Furthermore, 

it was observed that the time series of the numerical results matched the measurements very well. The comparisons to the 

measurements showed that a multibody drivetrain model captures the transient response behaviour of the wind turbine 

gearbox and is certainly a useful tool for load predictions. Unfortunately, only the measurements of the loads from the 

planetary stage were available for comparison. Future comparisons of the responses from the higher-speed stages will 

need to be made for further validation of the model.
7 

Figure 7: Emergency-shutdown event and its corresponding measured bearing loads

Figure 8: Start-up event and its corresponding measured bearing loads

Figure 9: Comparisons of the predicted planet bearing forces against the measurement results for the start-up and 

emergency-shutdown events.
8 

5. Detailed Model Study

5.1. Model Fidelity

This section describes a detailed drivetrain model fidelity study that was performed using the emergency-shutdown and 

start-up events as case studies. The maximum responses after the emergency brake was applied and during the start-up 

process were used for the comparisons.

Four different types of models were compared to the measurements in this section. The models are described as follows:

• GB00 – Fully rigid gearbox with tooth compliance and only torsional degrees of freedom

• GB01 – Fully rigid gearbox model with tooth compliance and bearing compliance

• GB02 – Addition of flexible shafts into GB01

• GB03 – Addition of flexible planet carrier into GB02

• GB04 – Addition of flexible housing and torque arms into GB03, making it a fully flexible model

The results are presented in Table 1 and Table 2. Responses that have large differences, i.e., above 20% or below minus 

20%, are highlighted in yellow. The results are presented as percentage differences versus the GB04 model using the

following formula:

04

04

% GB 100%

GB

X X difference X− = ×

( 1 )

where X is the response variable of concern and XGB04 is the response variable calculated from the GB04 model. The 

sampling rate is 200 Hz for the comparison presented in this section, whereas in Section 4, the sampling rate was 10 Hz. 

The results show that the tooth contact forces are not sensitive to the level of model detail. This means that a simplified 

model, i.e., GB00, can be used when only the gear contact forces are required. However, the gear contact forces here are 

the total integrated forces, and the load distribution along the tooth flank, i.e., face load factor, might be sensitive to the 

model fidelity. This was not investigated here because of the constraints of the model that was used. Future investigations 

into the face load factors should be conducted. On the other hand, the bearing forces at the low-, intermediate-, and highspeed shafts are sensitive to the gearbox model fidelity; the planetary stage bearings are less sensitive compared to these 

higher speed bearings. It was observed that the GB02 model is sufficient for the convergence of the planetary stage 

bearing loads. For the remaining higher-speed bearings, a GB04 model is required.
9 

Table 1: Comparison of Important Response Variables in the Entire Drivetrain from Various 

Computational Models (emergency shutdown event)

GB00 GB01 GB02 GB03

Gear contact forces

Sun-planet -9.38 8.14 -0.19 0.14

Intermediate speed -1.11 -1.46 0.10 0.20

High speed -2.51 -4.68 -0.42 -0.58

Bearing radial forces

PL-A -20.53 30.49 -9.06 -2.05

PL-B -22.99 -1.11 9.45 2.11

LS-SH-B 68.02 -9.56 146.02 150.41

LS-SH-C -22.74 -1.29 138.40 140.92

IMS-SH-B -19.29 31.11 -5.09 -1.78

IMS-SH-C 53.88 63.39 -26.63 -26.92

HS-SH-B 276.14 -51.98 -6.32 -0.80

HS-SH-C -10.04 47.16 17.36 9.74

Table 2: Comparison of Important Response Variables from Different Computation Models (start-up 

event)

GB00 GB01 GB02 GB03

Gear contact forces

Sun-planet 1.89 -0.10 0.66 0.50

Intermediate speed -2.88 -0.44 -0.38 -0.33

High speed -3.63 1.12 0.09 -0.04

Bearing radial forces

PL-A -17.32 -7.89 -3.46 1.61

PL-B -4.39 4.26 8.74 0.47

LS-SH-B 60.57 -5.33 17.54 17.70

LS-SH-C -33.97 -2.49 -1.56 -1.80

IMS-SH-B -41.52 -14.40 2.42 2.74

IMS-SH-C 98.46 50.37 -1.08 -1.14

HS-SH-B 42.43 -73.55 77.64 78.30

HS-SH-C -22.37 65.45 -2.34 -1.67
10

5.2. Flexible Modes

In this section, the flexible modes to be included in each flexible body were investigated. Each flexible mode consists of 

two state variables, one representing the displacement and the other representing the velocity. Using a larger number of 

flexible modes than required will increase the computational efforts required. The results in Section 5.1 show that the 

GB01 model is detailed enough for the calculation of the gear contact forces and that they did not benefit from the use of 

flexible bodies. Therefore, gear contact forces were not investigated in this section. The results are presented in Table 3

and Table 4 as percentage differences versus the GB04 model using Equation ( 1 ). 

The following notations are used in Table 3 and Table 4: 

• A10, A20 – 10, 20 elastic modes for all flexible bodies

• S10, S20 – 10, 20 elastic modes for all shafts and 40 elastic modes for the remaining flexible bodies

• S10, S20 – 10, 20 elastic modes for all shafts and 40 elastic modes for the remaining flexible bodies

• PC10, PC20 – 10, 20 elastic modes for the planet carrier and 40 elastic modes for the remaining flexible bodies

• H10, H20 – 10, 20 elastic modes for the housing and 40 elastic modes for the remaining flexible bodies

• TA10, TA20 – 10, 20 elastic modes for the torque arms and 40 elastic modes for the remaining flexible bodies

Comparing the results from Table 3 and Table 4 shows that the responses calculated under the emergency shutdown event 

are more sensitive to the number of modes included in the flexible bodies compared to the responses calculated under the 

start-up event. This suggests that the model requirements are dependent on the type of input loading to which the model is 

subjected. The reason for this can be explained by the differences in the nature of the main-shaft loads in each of the 

transient load events. In the emergency shutdown event, the maximum torque and bending moments experienced are

299.4 kNm and 168.6 kNm, respectively, while in the start-up event, the bending moments are 665.0 kNm and 195.5 

kNm, respectively. The bending moments are measured at a position that is about 70% of the main shaft length from the 

hub connection. In the emergency shutdown event, the ratio of the bending moment to torque is 0.56, while for the startup event it is 0.29. The higher ratio in the emergency shutdown event might demand a more flexible multibody model as 

the gears and shaft deflect more and therefore, are more sensitive to the prescription of the flexible bodies in the 

multibody model. A more thorough investigation considering more transient load events should be conducted to further 

validate this hypothesis.
11

Table 3: Comparison of Bearing Radial Forces in the Entire Drivetrain when Different Numbers of 

Elastic Modes are Used (emergency shutdown event)

Number of elastic modes A10 A20 S10 S20 PC10 PC20 H10 H20 TA10 TA20

PL-A -7.81 -5.70 -1.31 0.13 -6.61 -5.75 -0.26 -0.24 -0.23 -0.35

PL-B 7.27 5.42 0.11 -0.69 6.89 5.95 0.11 0.09 0.14 0.19

LS-SH-B 7.50 7.14 4.99 3.70 -0.22 -0.02 -0.69 -1.61 -0.12 0.20

LS-SH-C 17.16 27.85 11.95 7.82 0.58 0.43 -0.41 -1.17 0.40 0.41

IMS-SH-B -0.14 -0.88 -1.10 -0.21 -1.28 -1.34 -1.42 -1.84 -1.41 -1.40

IMS-SH-C 17.37 11.55 -13.24 -3.68 -2.96 1.76 26.24 14.64 3.58 2.17

HS-SH-B -51.62 -5.76 -31.69 0.91 0.09 0.07 -9.38 -8.34 1.62 0.62

HS-SH-C 35.66 -19.67 -17.08 -12.81 -0.61 -2.33 -3.06 -4.96 -10.99 -4.23

Table 4: Comparison of Bearing Radial Forces in the Entire Drivetrain when Different Numbers of 

Elastic Modes are Used (start-up event)

Number of elastic modes A10 A20 S10 S20 PC10 PC20 H10 H20 TA10 TA20

PL-A -2.31 -3.14 1.32 0.60 -4.64 -4.67 0.02 0.00 0.70 0.27

PL-B 7.10 5.34 -0.39 -0.95 7.67 6.76 -0.19 -0.29 -0.33 -0.32

LS-SH-B 5.08 0.07 4.88 -0.76 0.13 0.45 1.88 0.53 0.07 0.81

LS-SH-C -3.90 -1.37 -2.03 -0.14 -0.30 -1.25 0.11 -0.22 0.36 -0.71

IMS-SH-B 3.61 0.65 3.57 0.49 -0.50 0.25 1.87 0.53 0.47 -0.01

IMS-SH-C 1.01 1.22 -2.56 -0.87 -0.40 -0.29 0.10 -0.68 0.13 -1.28

HS-SH-B -2.55 7.49 -0.06 -0.45 -1.34 -1.07 -0.56 7.65 -2.46 -3.37

HS-SH-C 7.40 -6.81 9.26 -4.06 5.99 2.57 3.62 4.78 -3.68 0.11

6. Conclusions

A fully flexible model with 40 elastic modes reproduces the maximum loads experienced in the emergency shutdown and 

start-up events to within 3.2% and 2.0%, respectively. The time histories of calculated loads match the experiments. A 

fully rigid model would over predict the bearing loads by about 20%. The response variables at the higher-speed stages 

require a higher level of model fidelity to be represented correctly. The start-up event is not as sensitive as the emergency 

shutdown event to the number of modes in each flexible body. This might be because of the lower main shaft bending 

moment to torque ratio in the start-up event compared to the bending moment to torque ratio in the shutdown event. 

Acknowledgements

This work was financially supported by the Centre for Ships and Ocean Structures (CeSOS) at the Department of 

Marine Technology, Norwegian University of Science and Technology, Trondheim, Norway. The gearbox and wind 

turbine model were obtained from the Gearbox Reliability Collaborative (GRC) project at the National Renewable Energy 

Laboratory, Colorado, USA. The GRC initiative is funded by the Wind and Water Power Technologies Office, Office of 

Energy Efficiency and Renewable Energy, the U.S. Department of Energy under contract No. DE-AC02-05CH11231. 
12

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