Impact of User-Adjustable Vehicle-Dynamics Tuning on Vehicle Durability

Software-defined vehicles offer customers a greater degree of customization on vehicle operation. One such feature is a user-adjustable tuning of vehicle ride and handling, where customers can vary the ride height, the active damper stiffness (affecting ride comfort), front-rear torque balance (affecting ride handling), and other vehicle dynamics features. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than before, particularly when such tuning is extended to cover spirited “sport” mode driving, offroad driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability.  In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving beyond traditional durability methods that do not model a range of real-world usage behavior. The study has been conducted using one instrumented vehicle (RLDA) and anonymized telemetry data from over 20,000 Rivian customer vehicles. The study covers the impact of variations in ride height, damper stiffness of active dampers, and roll stiffness of the suspension. By combining usage frequency of the different settings with the damage accrued in these settings, the methodology estimates the high-cycle fatigue pseudo-damage variation for a wide range of customers, and compares real world damage risk with the damage accounted for in the baseline durability testing. Through the analysis we recommend a way to optimize the Accelerated Duty Cycle (ADC) for Over the Road (OTR) testing to minimize real-world risk, while keeping the duty cycle simple and practical for testing, i.e., test for an optimized combination of a few dominant settings and not a wide range of settings. The approach also suggests a path to a real-time fleet monitoring system to identify high-durability-risk customers and develop mitigation strategies.