CAE Optimizes Fatigue Life in Diesel Engine Crankshafts

Picture a heavy-duty truck navigating rugged mountain terrain, its engine roaring with power. Behind this seemingly simple scenario lies a critical component enduring unimaginable stress—the crankshaft. As one of the engine's core elements, crankshaft reliability directly impacts overall machine performance and longevity. But how can engineers ensure stable operation under extreme conditions while preventing catastrophic fatigue failures?

In internal combustion engines, crankshafts perform the vital function of converting piston reciprocating motion into rotational force that powers vehicles and equipment. Working in concert with cylinder heads, connecting rods, camshafts, and engine blocks, crankshafts endure complex, repetitive dynamic loads throughout their service life.

These loads include forces generated by cylinder combustion pressure and inertial forces from uneven mass distribution. Structural features like crankpin fillets and oil holes create stress concentration zones—prime locations for potential fatigue failure. As the most common failure mode in crankshafts, fatigue fractures can cause severe engine damage and potentially dangerous accidents, making reliability verification essential.

Modern design challenges—including demands for higher payload capacity, lighter weight, improved efficiency, and shorter load cycles—have intensified pressure on crankshaft engineering. Traditional design methods relying on experience and physical testing prove both time-consuming and costly. Computer-Aided Engineering (CAE) analysis now enables performance prediction and optimization during early design phases, significantly reducing development timelines while enhancing reliability.

This research presents a comprehensive CAE-based development approach for four-cylinder diesel engine crankshafts, spanning from conceptual design to final validation. The methodology incorporates these key analytical stages:

• Free Vibration Analysis: Determines natural frequencies and mode shapes to adjust modal parameters and prevent resonance conditions that could amplify vibration and accelerate fatigue.
• Bending/Torsional Stiffness Analysis: Evaluates each crank throw's resistance to deformation, as insufficient stiffness can impair engine performance and lifespan.
• Stress Concentration Factor (SCF) Calculation: Identifies localized stress peaks at critical fillet regions, where fatigue failures typically originate.
• Transient Dynamics Analysis: Simulates complete cranktrain system behavior (including flywheel and pulley) under operational conditions to map stress distribution patterns.
• Fatigue Life Assessment: Uses stress results from transient analysis to predict service life through specialized software (e.g., FEMFAT), informing design and maintenance strategies.

3.1 Load Application and Boundary Conditions

Precise load simulation forms the foundation of accurate CAE analysis. Researchers apply cylinder-specific forces according to firing sequences, modeling two full crankshaft rotations to cover all combustion events. Derived from pressure-crank angle (P-θ) diagrams, dynamic loads are implemented as angular/time-dependent functions at corresponding locations. The rotational cycle divides into 360 increments for detailed resolution.

Boundary conditions replicate actual installation constraints—main bearing journals receive fixed or bearing-type supports to simulate engine block connections. Additional considerations include lubricating oil film effects, which reduce friction while influencing vibration characteristics.

3.2 Free Vibration Analysis

This phase identifies natural vibration frequencies and corresponding mode shapes without external excitation. Using finite element methods, analysts discretize the crankshaft into computational elements to solve motion equations. Results guide structural adjustments—modifying stiffness or mass distribution—to shift natural frequencies away from operational excitation ranges and avoid resonance.

3.3 Bending and Torsional Stiffness Evaluation

As critical indicators of deformation resistance, bending and torsional stiffness values are calculated through finite element simulations applying moment or torque loads. Excessive deformation from insufficient stiffness can compromise cylinder sealing (bending) or reduce power output (torsion). Findings inform dimensional or material optimizations to enhance rigidity.

3.4 Stress Concentration Factor Determination

Geometric discontinuities like fillet transitions and oil holes create localized stress intensification—the primary driver of fatigue failure. SCF values (ratio of peak to nominal stress) are derived through refined finite element meshing and stress field calculations. Results guide geometric improvements such as enlarged fillet radii or optimized transition profiles to mitigate stress concentrations.

3.5 Transient Dynamic Simulation

This advanced analysis captures time-dependent system behavior including inertial, damping, and nonlinear effects. Complete cranktrain models incorporate connecting rods, pistons, flywheels, and pulleys. Simulating real-world scenarios—startup, acceleration, deceleration—the analysis generates displacement, velocity, acceleration, and stress histories for fatigue evaluation.

3.6 Fatigue Life Prediction

Using transient stress histories as input, fatigue analysis software applies S-N or ε-N curve models to calculate cumulative damage from cyclic loading. When damage accumulation reaches critical thresholds, failure occurs. This predictive capability informs design life expectations and maintenance schedules.

CAE results enable data-driven determination of dimensional specifications, material selection, and heat treatment processes. Structural optimizations may include crank web profile modifications, enhanced fillet designs, or mass reduction strategies. Engineers must also coordinate crankshaft parameters with adjacent components—connecting rod geometry, flywheel mass properties—to ensure system compatibility.

This CAE-based methodology provides comprehensive crankshaft performance assessment from initial concept through final validation. Integrating vibration analysis, stiffness evaluation, stress concentration mapping, transient dynamics, and fatigue prediction enables targeted optimizations that reduce development time and cost while improving reliability. As CAE technology advances, its expanding role in crankshaft design will continue driving innovation in engine performance and durability.