1. MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING
Dr. Jiankun Yuan
Prof. Yiming (Kevin) Rong
Acknowledgement: This project is partially supported by Delphi and CHTE at WPI. Dr. Q. Lu was involved in the early work of the project.

2. Induction: Why Induction Heat Treatment?
Advantages
Greatly shortened heat treatment cycle
Highly selective
Highly energy efficiency
Less-pollution process
Practical Problems
Lack of systematic heating time and temperature distribution control inside WP.
Nonlinear effect of material properties.
Lack phase transformation data inside WP for hardness and residual stress determination.
Evaluate combination effect of AC power density, frequency and gap on final hardness pattern.
Trial and error, cost and design period.
Research content: FEM based electromagnetic/thermal analysis
+ quenching analysis + hardening analysis
Numerical modeling may provide better prediction
Research objective: (1) Provide T field, time history inside WP
(2) Determine formed content of martensite, pearlite and bainite.
(3) Determine hardness distribution in WP.
(4) Guidance for induction system design.

3. Introduction: Induction Hardening Process
Induction heating: metal parts heated to austenite Phase
Fast quenching process transforms austenite to martensite phase
workpiece
Inductor/coil
Heating process
Martensite content determines the hardness
Joule heat by
eddy current
Martensitic structure is the most hardest microstructure
Electromagnetic field
High freq. AC power
Induction
coil

4. Principle: Electromagnetic and Thermal Analysis
Coil WP
Electromagnetic Analysis
Thermal Analysis with finite element model
Input AC power to coil
QC
QEt QN QW QS
QB QE
QR+ QCV
(Outside)
(a) WP geometry
(b) FEA model
(c) Interior element
(d) Surface element
Calculation of
magnetic vector potential (A)
Calculation of
magnetic flux density (B)
B =   A
(Gauss’ Law for
magnetic field)
Calculation of
magnetic field intensity (H)
H = B / 
Calculation of
electric field intensity (E)
(Faraday’s Law)
Calculation of
electric field density (D)
D =   E
Calculation of
current density (J)
(Ampere’s Circuital Law)
Heat conduction
Calculation of
Inducting heat (Qinduction)
Qinduction = E  J = J2/
Output:
Heat generation Qinduction in WP
Induced Joule heat
Heat radiation
Heat convection

5. Case Study: Complex Surface Hardening
concave
Material: Carbon Steel, AISI 1070
convex
Automotive parts from Delphi Inc., Sandusky,Ohio
Concave and convex on surface of workpiece make the heating process not easy to control.
Real spindle to be hardened
Geometry Model
ANSYS system is employed for the analysis.
Mesh should be much finer at locations of convex and concave in both coil and workpiece.
FEA model and B.C.
Mesh generated by ANSYS

6. Case Study: Material Properties -- AISI 1070
(a) Electromagnetic Properties
conductivity
WP relative
permeability
Electrical
Resistivity
(b) Thermal Properties
Emissivity
Specific
heat
Convection
coefficient

7. Case Study: Magnetic Field Intensity Distribution

8. Effect of current density distribution
Constant current distribution in coil can not result in good heating pattern, especially at concaves of workpiece
Better hardened pattern resulted from modification of Finer coil mesh and enhanced coil current density at area neighboring to surface concaves of workpiece.
Enhanced coil current density suggests utilization of magnetic controller at those area in coil design process. Physically this can be fulfilled by magnetic controller.
(a1) Constant current distribution in coil (a2) heated pattern
(b1) Adjusted current distribution in coil (b2) heated pattern

9. Case Study:Temperature Variation with Time in Induction Heating Process
t=0.5s
t=2s
Total heating time th = 7.05s
f=9600Hz s=1.27mm J=1.256e6 A/m2
t=4s

10. Case Study: Heating Curves
Summary
• A finite element method based modeling system is developed to analyze the coupled electromagnetic/thermal process in induction heating and implemented in ANSYS package, with following capabilities.
• Provide electrical and magnetic field strength distribution.
• Provide instantaneous temperature field data in workpiece.
• Provide Temperature history at any location in heating process.
• Provide guidance for inductor/coil design based on adjustment of current density distribution and desired heating patterns.