Research Focus Area 2

Principal Investigator: Chris Edrington

Motivation: Advanced modeling, control methodologies, power electronics, electrical power delivery architectures, high-speed simulation, HIL and understanding of degradation of components are critical in the development of NGCV

Goal: Develop reconfigurable power delivery architectures; power electronics enablers; HPC-based computing environment; cyber secure hardware and degradation abatement strategies

Approach: Exploring options for reconfigurable power architectures; modeling 2-level PEBB (power electronic building blocks for architecture enabling); modeling PEBB devices in HPC; cyber-secure power hardware; using Evidence Theory and Markov chains for degradation abatement algorithms

Principal Investigator: Joshua Tong

Motivation

• High volumetric and mass power density
• Intermediate-temperature operation (400- 700 °C)
• Flexible fuels (JP-8, hydrocarbons, biomass-derived fuels)

Goal: Develop an elevated-temperature all-solid-state Li-ion battery

Approach

• Materials computation, synthesis, and characterization
• Device component design, fabrication, and characterization
• Device modeling, design, manufacturing, and testing

Principal Investigator: Stephen Creager

Motivation

• High power/ high energy density

• High-temperature operation (suitable for 1050 °C cooling)

• Safe (i.e., nonflammable, operates after physical damage)

Goal: Develop an elevated-temperature all-solid-state Li-ion battery

Approach

• Materials computation, synthesis, and characterization
• Device component design, fabrication, and characterization
• Device modeling, design, manufacturing, and testing

Principal Investigator: Benjamin Lawler

Motivation

• Future unmanned military ground vehicles have unique powertrain requirements that are distinct from commercial on-road vehicles
• Military applications require high-power-density engines, have challenges associated with heat dissipation, and will be hybridized to meet electrical demands
• To meet these unique requirements, alternative combustion strategies, unconventional engine designs, and/or unique powertrain layouts may be required

Goal: Develop a simulation framework for engine and powertrain layout design to assess the suitability of various combustion strategies and powertrain layouts for different military applications, including experimental validation and hardware-in-the-loop (HIL) evaluation

Approach: Construct MATLAB/Simulink and GT-Suite models of various engine architectures and powertrain layouts, and developa  facility for HIL validation and demonstration

Principal Investigator: Robert Prucka

Motivation

• 'Look-ahead' energy demand is available on autonomous vehicles
• Can be used to improve transient control of electro-mechanical power systems, especially in cooling-constrained situations

Goal

• Control algorithms that utilize energy preview information to simultaneously balance fuel consumption, electrical energy demand, ground performance and heat rejection
• Provide powertrain ‘availability’ for upcoming events

Approach: Real-time artificial intelligence-based optimization utilizing forward-looking autonomous vehicle perception information

Principal Investigator: Beshah Ayalew

Motivation

• Fully burdened fuel cost is 100’s X that of civilian applications
• On-board electrical energy is now critical for various ISR, navigation and warfighter equipment

Goal

• Develop optimal energy sharing and utilization strategies for fleets of vehicles of varying scales operating in a resource-constrained environment
• Incorporate mobile/movable microgrids involving tactical vehicles

Approach

• Develop computable models and algorithms for energy-optimal motion plans for UGVs and UAVs
• Devise optimal design and operational control schemes for microgrids that support these vehicles while ensuring stable operation

Principal Investigator: Shuangshuang Jin

Motivation: System modeling of electrified powertrains to understand the behaviors and interactions of each dynamic component is critical to the virtual prototyping of ground vehicle systems

Goal: Develop a high-performance computing-based high-fidelity powertrain co-simulation framework featuring high modular capability, scalable interface, concurrent execution, synchronized communication, and fast computation

Approach: Identify powertrain co-simulation use cases; declare I/O interfaces and interconnections; design Julia computing and HELICS-based co-simulation framework; develop hierarchical, distributed, and parallel simulations

Principal Investigator: Benjamin Lawler

Motivation: There is a need for an integrative effort across the VIPR-GS center to combine component submodels for engines, powertrain layouts and controls, energy storage devices, and power electronics

Goal: Develop a hardware-integrated virtual environment (HIVE) that can explore vehicles of varying scale, simulate powertrain architectures and their control strategies, and evaluate certain hardware components over mission profiles based on virtual vehicle characteristics

Approach: Collect propulsion system subcomponent models from the VIPR-GS center, integrate them into digital twins of military vehicles, and conduct HIL evaluations where either the virtual or physical components can be the subject of investigations

Principal Investigator: Apparao Rao

Motivation: To successfully develop high-temperature batteries with the desired architecture, it is essential to integrate experimental research with computational modeling over all relevant length scales from atomic-scale to continuum-scale

Goal: Develop multi-scale modeling frameworks for high-temperature battery cells and packs

Approach

• Elucidate the interface structures via experiments, atomic-scale and continuum-scale models
• Construct cell-level models to study the device performance using a bottom-up approach
• Derive pack-level degradation models

Principal Investigator: Qilun Zhu

Motivation: Maximize off-road vehicle performance by combining powertrain and mobility control, considering perception uncertainties

Goal

• Short-horizon predictive control coordinating powertrain, steering, and braking​
• Stochastic optimal control algorithm​
• Parallel computation for faster execution​

Approach

• Integrated simulation of vehicle dynamics, powertrain, and 3D environment​
• Stochastic Model Predictive Control and data-driven methods​
• Robust vehicle dynamics observer​
• Algorithm parallelization and controller-in-the-loop testing​
• Validation on Deep Orange 15

Principal Investigator: Benjamin Lawler

Motivation: Evaluate the hybrid powertrain performance associated with several high-power-density engine architectures. Continue modeling high-power-density engines using reduced-order models and CFD/FEA, and collect experimental validation data when needed. Determine the impact of engine operating conditions on the maximum and total heat flux through the piston crown at extreme operating conditions.

Goal: More info to come

Approach: More info to come

Principal Investigator: Ramakrishna Podila

Motivation: By leveraging the knowledge and capabilities acquired in the previous development of thermal conductive composite materials for NASA missions, our effort is aimed at the delivery of technology based on nanoscale boron nitride-derived materials with high isotropic thermal conductivity for battery thermal management applications.

Goal: More info to come

Approach: More info to come

Principal Investigator: Apparao Rao

Motivation: Develop new electrolyte formulations for low-temperature batteries.

Goal: More info to come

Approach: More info to come

Principal Investigator: Robert Prucka

Motivation: Develop hybrid electric powertrain control strategies for safe operation in extreme ambient temperatures.

Goal: More info to come

Approach: More info to come

Principal Investigator: Joshua Tong

Motivation: More info to come

Goal: More info to come

Approach: More info to come