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A linear parameter varying (LPV) reduced order model (ROM) is used to approximate the volume-averaged temperature of battery cells in one of the modules of the battery pack with varying mass flow rate of cooling fluid using uniform heat source as inputs. The ROM runs orders of magnitude faster than the original CFD model. To reduce the time it takes to generate training data, used in building LPV ROM, a divide-and-conquer approach is introduced. This is done by dividing the battery module into a series of mid-cell and end-cell units. A mid-cell unit is composed of a cooling channel sandwiched in between two half -cells. A half-cell has half as much heat capacity as a full-cell. An end-cell unit is composed of a cooling channel sandwiched in between full-cell and a half-cell. A mass flow rate distribution look-up-table is generated from a set of steady-state simulations obtained by running the full CFD model at different inlet manifold mass flow rate samples.

As one of many pack-level battery simulation approaches developed within the General Motors-led Computer-Aided Engineering of Automotive Batteries (CAEBAT) Phase 1 project, the system approach treats the entire battery pack as a dynamic system which includes multiple engineering disciplines for simulation. It is the most efficient approach of all the CAEBAT battery pack-level approaches in terms of computational time and resources. This paper reports the application of the system approach for a 24-cell liquid-cooled prototype battery pack. It also summarizes the verification of the approach by comparing the simulation results with the measurement data. The results using the system approach are found to have a very good agreement with the measurements.

Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

Fuel economy and stringent emissions requirements have steered the automotive industry to invest in advanced propulsion hybrids, including Plug-in hybrid vehicles (PHEV) and Fuel cell vehicles. The choice of battery technology, its power and thermal management and the overall vehicle energy optimization during different conditions are crucial design considerations for PHEVs and battery electric vehicles (BEV). Current industry focus is on Li-Ion batteries due to their high energy density. However, extreme operating temperatures may impact battery life and performance. Different cooling strategies have been proposed for efficient thermal management of battery systems. This paper discusses the modeling and analysis strategy for a thermally managed Lithium Ion (Li-Ion) battery pack, with coolant as the conditioning medium.

The thermal behavior of a fluid-cooled battery can be modeled using computational fluid dynamics (CFD). Depending on the size and complexity of the battery module and the available computing hardware, the simulation can take days or weeks to run. This work introduces a reduced-order model that combines proper orthogonal decomposition, capturing the variation of the temperature field in the spatial domain, and linear time-invariant system techniques exploiting the linear relationship between the resulting proper orthogonal decomposition coefficients and the uniform heat source considered here as the input to the system. After completing an initial CFD run to establish the reduction, the reduced-order model runs much faster than the CFD model. This work will focus on thermal modeling of a single prismatic battery cell with one adjacent cooling channel. The extension to the multiple input multiple output case such as a battery module will be discussed in another paper.