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AMESim Heat Generation Model

CAViDS Consortium. AMESim Heat Generation Model. A CAViDS Consortium Project. Advisory Board Report July 21, 2011. CAViDS Consortium. Project Objective. Develop AMESim heat generation modeling capability for gearbox systems which compares favorably with experimental results.

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AMESim Heat Generation Model

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  1. CAViDS Consortium AMESim Heat Generation Model A CAViDS Consortium Project Advisory Board Report July 21, 2011

  2. CAViDS Consortium Project Objective • Develop AMESim heat generation modeling capability for gearbox systems which compares favorably with experimental results.

  3. CAViDS Consortium Work Plan Phase 1: Obtain software and familiarize. (Complete) Phase 2: Model and correlate churning and gear heat generation and temperature rise. 1. Caterpillar FZG test stand model (Complete) 2. Eaton heavy duty transmssion (Underway) 3. Eaton medium duty transmission (Underway) 4. Caterpillar Axle model (Waiting for data)

  4. CAViDS Consortium Technical Status 1. Correlated AMESim temp rise model with Caterpillar Dynasty model of FZG test stand Correlated AMESim temp rise model with Eaton MDT and HDT test data Correlated Changenet based spreadsheet no load loss prediction with MDT and HDT test data Compared AMESim and Changenet churning loss predictions Compared AMESim, LDP, Benedict Kelley, ISO and other sliding loss predictions

  5. CAViDS Consortium Goals for Last Month • Continue to refine no loss modeling techniques • Evaluate alternative gear sliding models • Incorporate Changenet churning submodel in AMESim

  6. CAViDS Consortium Last Month’s Accomplishments • Further refined spreadsheet for Changenet prediction of churning losses for MD and HD transmissions (Complete) • Compared various sliding loss prediction techniques (Complete) • Incorporated single gear Changenet churning loss model into AMESim (Complete) • Wrote status report

  7. CAViDS Consortium No Load Loss Model Develop heat generation modeling capability for Eaton medium and heavy duty which accurately predicts no load losses and temperature rise on a spin test.

  8. CAViDS Consortium Loss Prediction Approach Considered following losses 1. Churning - Use Changenet approach 2. Oil shear – Use standard shear formula 3. Bearing – Harris reference

  9. CAViDS Consortium Changenet Churning Loss Equations Loss = C/2 * oil density * speed^2 * pitch radius^3 * submerged area Did not use C = 1.366 * (submerged depth/pitch diameter)^0.45 * (oil volume/pitch diameter^3)^0.1 * Froude^-0.6 * Re^-0.21 Re < 6000 C = 3.644 * (submerged depth/pitch diameter)^0.1 * (oil volume/pitch diameter^3)^-0.35 * Froude^-0.6 * (tooth thickness/pitch diameter)^0.85 Re > 6000 • Key assumptions: • Submerged area is defined by dynamic oil height and circumferential submerged area of gear (submerged arc length times gear width). • Reynolds number is peripheral gear speed times gear tooth width divided by kinematic oil viscosity at temperature • Froude number is peripheral gear speed divided by gear tooth width times gravity

  10. CAViDS Consortium Oil Shear Loss Prediction Torque Loss = (S * R * v * A) / d S = speed differential (gear and synchronizer) – m/sec R = synchronizer gage radius - m v = dynamic viscosity of oil – kg/(m*sec) A = synchronizer area – m^2 d = gap between gear and synchronizer - m Torque on drive gear reacted through MS and CS

  11. CAViDS Consortium Bearing Viscous Loss Prediction Viscous Torque = f*(v*n)^0.6667 * d^3 f = constant depending on bearing type v = viscosity in cs n = bearing speed in rpm d = mean bearing diameter in mm

  12. CAViDS Consortium Current Prediction ResultsMedium Duty

  13. CAViDS Consortium Current Prediction ResultsHeavy Duty DirectNormal Fill

  14. CAViDS Consortium Current Prediction ResultsHeavy Duty Direct2 Inch Overfill

  15. CAViDS Consortium Current Prediction ResultsHeavy Duty Direct2 Inch Underfill

  16. CAViDS Consortium AMESim Single Gear Set Churning Loss Sub-Model

  17. CAViDS Consortium HDT Gear Sliding Loss Prediction • Developed spreadsheet based on Kahraman 2007 paper using LDP predicted loads and sliding speeds • Compared to various approaches to calculate sliding losses and old experimental results using spreadsheet values • Selected best approach

  18. CAViDS Consortium Gear Mesh Loss Prediction Approach • Use LDP to calculate gear load, sliding and rolling velocity vs. roll angle • Use various empirical formulas to determine friction coefficient vs. roll angle • Calculate losses vs. roll angle • Determine average loss through mesh • Correlate with temp rise testing based on model

  19. CAViDS Consortium Sliding Loss Comparison • LDP has incorrect relationship with temperature • Benedict-Kelley to too sensitive to surface finish • AMESim and Misharin have no surface finish effect • ISO agrees well with experiment and has reasonable sensitivity to temperature and surface finish

  20. CAViDS Consortium Sliding Loss Comparison ( Load Intensity * Surface Finish) Effective Radius * Rolling Velocity * Dynamic Viscosity ) ^ 0.25 0.12 *

  21. CAViDS Consortium Next Month • Incorporate synchro shear and bearing losses into AMESim • Develop axle churning loss model • Develop axle thermal model

  22. CAViDS Consortium Notes • Software easy to use • LMS has great support • Capabilities will meet our needs • University license $3000 for year • Changenet churning loss calculations look promising • LDP mesh loss prediction easy to use – need development

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