Traction Efficiency Mapping via Pressure–Shear Coupling Analysis

At its core, traction efficiency mapping recognizes that soil doesn’t behave like a rigid foundation: when a tire rolls, vertical pressure compresses soil vertically while shear forces push it laterally. If those forces act independently, models fail—because soil strength depends on *both*: its cohesion (c) and internal friction (φ), governed by τ ≤ c + σ_z·tanφ. Early empirical models treated traction as a simple function of weight and coefficient of friction—but ignored how pressure redistributes *during* shear, causing localized densification or fluidization.

Modern coupling analysis treats the tire–soil interface as a boundary-value problem. Finite element models embed realistic tire carcass stiffness (from laser-scanned geometry and cord angle data) and soil constitutive laws calibrated from triaxial or simple shear tests. Critical advances include modeling rate-dependent behavior (e.g., using Perzyna viscoplasticity) and incorporating soil–tire interlocking via discrete element co-simulation (e.g., EDEM + Abaqus). This captures lug penetration dynamics and lateral soil ejection—key drivers of shear resistance not captured by continuum-only approaches.

The highest-fidelity implementations integrate real-time GNSS-RTK position, IMU-derived slip angle, and in-tire pressure sensors to update the pressure–shear map every 100 ms. These digital twins feed closed-loop controllers that adjust engine torque or differential lock in response to predicted η gradients—transforming traction from a static design parameter into a dynamically regulated process. Recent validation at the USDA-ARS Coshocton facility confirmed that such systems reduce fuel use by 9.3% and subsoil compaction (≤0.5 m depth) by 31% compared to fixed-pressure operation.