Speed Profile Generation for a Dual Motor Equipped Electrified Series Hybrid Tracked Vehicle Through Dynamic Programming Based Energy Optimization Procedure

Gocer, Ismail; Baslamisli, S. Caglar · 2024 · Crossref

DOI: 10.1007/978-3-031-70392-8_63

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Summary

This paper addresses the challenge of optimizing energy efficiency and trip time for dual-motor, series hybrid tracked vehicles. While electrification is increasingly researched in tracked vehicles, existing studies often focus on straight-road conditions or apply Dynamic Programming (DP) in the time domain with predefined speed profiles. This work introduces a spatial domain DP approach to generate optimized speed profiles for predefined road geometries, specifically accounting for the unique dynamics of skid-steered tracks. Unlike wheeled vehicles, tracked vehicles must overcome significant turning resistance moments during steering maneuvers, where the inner track brakes while the outer track provides traction. The study aims to balance fuel economy against trip time optimality by considering these specific mechanical constraints. The methodology employs a five-dimensional Dynamic Programming framework with states defined by distance, longitudinal velocity, and battery State of Charge (SoC), and control inputs defined by longitudinal acceleration and alternator torque. The model incorporates kinematic relations for skid steering, estimating required motor torque and power demand based on road inclination, turning radius, and inertial moments. The cost function minimizes a weighted sum of trip time, fuel consumption, and power losses from the battery and motors, subject to physical constraints such as maximum velocity, acceleration limits, and battery current limits. The internal combustion engine operates at a rated speed, while the alternator adjusts torque to meet power demands, with the battery handling surplus or deficit power. The results are demonstrated on a short, predefined road profile featuring straight sections, curves, and 10% uphill and downhill gradients. Three solutions were generated with different weighting factors for time versus fuel economy. Solution 1 prioritized speed, resulting in a duration of 32.09 seconds and 151.0 ml fuel consumption. Solution 3 prioritized fuel economy, taking 33.27 seconds and consuming 148.8 ml. Powertrain analysis revealed that aggressive alternator usage in faster solutions increased fuel consumption, while battery charging occurred during braking phases and before curve sections. The final SoC and velocity returned to their initial values (~60% and ~5 km/h) as enforced by the DP boundary conditions. The significance of this work lies in its application of spatial domain DP to tracked vehicles, explicitly modeling the energy penalties associated with skid steering. It provides a framework for generating optimal speed profiles that account for complex terrain and vehicle dynamics, offering insights into the trade-offs between operational speed and energy efficiency. This approach supports the development of more efficient control strategies for electrified tracked vehicles, particularly in scenarios involving mixed road geometries.

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• speed choice