Semester

Summer

Date of Graduation

2026

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Lane Department of Computer Science and Electrical Engineering

Committee Chair

Brian Woerner

Committee Member

Andrew Nix

Committee Member

Parviz Famouri

Abstract

Battery electric vehicle performance depends on both powertrain efficiency and battery-health. In dual-motor all-wheel-drive battery electric vehicles, driver-requested torque can be distributed between front and rear electric drive units, creating an opportunity to reduce electrical energy demand through torque allocation. However, lithium-ion battery aging changes the electrical behavior of the energy storage system through capacity fade and internal resistance growth. Capacity fade reduces the usable energy and vehicle range, while resistance growth increases voltage drop, current-related losses, and battery electrical loading. This thesis evaluates how these degradation effects influence the energy consumption, simulated range, and battery electrical behavior of optimized torque splitting in a dual-motor all-wheel-drive battery electric vehicle.

The studied vehicle model uses a front induction-motor electric drive unit, a rear permanent-magnet electric drive unit, and a modeled lithium-ion battery pack. Battery degradation is modeled using representative healthy, degraded, and late-life battery cases. The degraded and late-life cases reduce the battery capacity parameter and increase pack resistance while retaining the baseline state-of-charge/open-circuit voltage relationship. Additional capacity-only and resistance-only cases are used to isolate the separate effects of capacity fade and resistance growth.

An offline exhaustive-search optimization method is developed to generate front and rear torque-split maps. Candidate torque splits are evaluated using electric drive unit loss maps, battery electrical calculations, and feasibility constraints. The optimized split is implemented as a three-dimensional lookup-table in the vehicle controller and compared against two fixed torque-split baselines: a capability-weighted fixed split and a mean-matched fixed split selected to approximate the average rear permanent-magnet electric drive unit bias of the optimized strategy.

Simulation results are evaluated over an SAE J1634 SMCT+-derived drive-cycle procedure using full-charge single-cycle, low-state-of-charge, isolation-case, and repeated endurance simulations. The exhaustive-search optimized split is generally biased toward the rear permanent-magnet electric drive unit, with mean optimized permanent-magnet torque share in the low-to-mid 60% range. In full-charge single-cycle testing, the optimized strategy reduces energy consumption from 337.35 Wh/mi for the capability-weighted split to 331.49 Wh/mi in the healthy case. In endurance testing, the optimized strategy provides the longest simulated range in each battery-health case, reaching 326.36 miles for the healthy case, 295.08 miles for the degraded case, and 275.34 miles for the late-life case.

The results show that optimized torque splitting provides a modest but repeatable energy and range benefit across battery-health conditions. However, the range loss caused by capacity fade is larger than the range recovered through torque optimization. The isolation cases show that capacity fade primarily reduces remaining state of charge and endurance margin, while resistance growth primarily increases estimated  loss and affects voltage/current behavior. These findings support evaluating torque-split strategies under degraded battery conditions and using battery electrical behavior metrics in addition to energy consumption and range.

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