Fuel-Optimal Strategies for Vehicle Supported Military Microgrids

2016-01-0312

04/05/2016

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
Vehicles with power exporting capability are microgrids since they possess electrical power generation, onboard loads, energy storage, and the ability to interconnect. The unique load and silent watch requirements of some military vehicles make them particularly well-suited to augment stationary power grids to increase power resiliency and capability. Connecting multiple vehicles in a peer-to-peer arrangement or to a stationary grid requires scalable power management strategies to accommodate the possibly large numbers of assets. This paper describes a military ground vehicle power management scheme for vehicle-to-grid applications. The particular focus is overall fuel consumption reduction of the mixed asset inventory of military vehicles with diesel generators typically used in small unit outposts. By exploiting peak efficiency operation of the diesel generators and the vehicle’s energy storage systems, the total fuel consumption can be reduced over a typical daily outpost load cycle. While military vehicle energy storage requirements are dominated by silent watch objectives, this work adds another dimension to the objective set to include outpost fuel consumption. Motivated by these requirements, an extensible MATLAB/Simulink simulation of the system was constructed using the complex nodal admittance matrix approach to connect stationary diesel generators and vehicles with two-way power flow for either supporting the power grid or acting as a load for charging their batteries. After describing the model and energy management strategy, simulation studies are used to illustrate the approach using both idealized and measured outpost load data.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-0312
Pages
9
Citation
Jane, R., Parker, G., Weaver, W., and Rizzo, D., "Fuel-Optimal Strategies for Vehicle Supported Military Microgrids," SAE Technical Paper 2016-01-0312, 2016, https://doi.org/10.4271/2016-01-0312.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-0312
Content Type
Technical Paper
Language
English