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Thermal Analysis of Parallel Connected Li-Ion Batteries For Hybrid Aircraft

Anadolu University-Hikmet Karakoç
Howard University-Nadir Yilmaz
  • Technical Paper
  • 2020-01-0891
To be published on 2020-04-14 by SAE International in United States
Improving the energy performance of batteries will certainly increase the reliability of electric aircraft and thus their penetration into the market. To achieve this goal, battery management systems are required to keep the temperature below the safety limits and make the temperature distribution as even as possible within the battery pack and cells. Li-ion batteries are suitable for electric aircraft due to their high specific energy and advantage of energy density. In this study, 20 14.6 Ah prismatic batteries were connected in 2 parallel 10 series. Three-dimensional thermal analysis was performed for forced and natural transport conditions under 4 different discharge rates (0.5C, 1C, 2C, 2.5C) of the batteries. The study was conducted with Ansys Fluent. The NTGK Empirical model was chosen and a simple algorithm was used. A second order upwind method was chosen for pressure, momentum and energy equations. Batteries were tested for mesh independency. When the number of nodes in natural transport was increased from 43,204 to 345,560, the change in heat transfer was 0.1%. As the current rate given to the…
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Mechanical response of laterally-constrained prismatic battery cells under local loading

Tsinghua University-Feiyu Xiao, Bobin Xing, Yong Xia
  • Technical Paper
  • 2020-01-0200
To be published on 2020-04-14 by SAE International in United States
The crash safety of prismatic lithium-ion batteries has received great attention in recent years because of their growing popularity in electric vehicles. However, the safety issues of prismatic batteries have not been thoroughly studied, in particular, the mechanical responses of prismatic battery cells with lateral constraints under varied loading conditions remain unclear. In this study, a fixture for lateral constraint based on the real packing situation in module is conducted to investigate the mechanical responses of prismatic battery cell in intrusion tests. Firstly, the effects of loading conditions, namely, the type and loading position of the indenters, and the impact speed, on coupled mechanical, electrical and thermal responses of prismatic battery cells are analyzed and discussed. Secondly, the influence of the side deformation of the impacted battery cell on the electrochemical performance of adjacent battery cells is studied. Therefore, the response of the packed batteries under local loading is revealed, which aims at helping the post-accident treatment of the battery module of electric vehicles. Thirdly, a simplified finite element model of packed prismatic battery cells…
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PHEV hybrid vehicle system efficiency and battery aging optimization using A-ECMS based algorithm

FCA USA LLC-Yang Liang, Sandeep Makam
  • Technical Paper
  • 2020-01-1178
To be published on 2020-04-14 by SAE International in United States
Minimizing lithium ion battery aging and maximizing overall system efficiency are key engineering design objectives for plug-in electric hybrid vehicles (PHEVs). To quantitatively optimize the aging and system efficiency, an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) based optimization method is implemented within vehicle simulation code. Battery charge and discharge cycling is modeled using equivalent circuit modeling techniques where circuit parameters are updated based on estimated aging effects. These aging effects are predicted through a so-called single particle model wherein particle interactions are neglected, and solid electrolyte interface (SEI) layer aging is predicted for graphite anode. The proposed aging model is calibrated against available battery aging data for similar batteries. Steady state capacity fade map under given environmental conditions and various battery states of charge and current levels are predicted. A battery capacity fade map is generated, and then used in the AECMS optimization function to adjust aggressiveness of the PHEV power split decisions. The results of a single objective (pure efficiency based), and a multi-objective (battery aging and efficiency are weighted to form an objective…
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A Dynamic Programming Algorithm for HEV Powertrains Using Battery Power as a State Variable

FCA US LLC-Omkar Rane, Krishna Madireddy, Bryon Wasacz
McMaster University-Lucas Bruck, Adam Lempert, Saeed Amirfarhangi Bonab, Jeremy Lempert, Atriya Biswas, Joel Roeleveld, Ali Emadi
  • Technical Paper
  • 2020-01-0271
To be published on 2020-04-14 by SAE International in United States
One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery State of Charge (SOC) makes this state vector a heavy variable. As things move fast in the industry, a rapid tool with the same performance is required. The present work proposes a novel approach in defining the state variables of the DP algorithm with the objective of reducing the computational time at a low cost of…
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A Method for Simultaneous State of Charge, Maximum Capacity and Resistance Estimation of a Li-Ion Cell Based on Equivalent Circuit Model

Auburn University-Saurabh Gairola, Yang Hu
  • Technical Paper
  • 2020-01-1182
To be published on 2020-04-14 by SAE International in United States
Accurate estimation of the State of Charge (SOC), maximum capacity (Qmax) and internal resistance are critical for battery monitoring, i.e., determining the status, health, and performance figures of a battery. SOC is a key indicator of the instant status for battery systems, while Qmax and internal resistance are related to the capacity fade (SOHQ) and power fade (SOHP) respectively, which represent the abilities of a battery to store energy, retain charge over extended periods and provide the required power for acceleration, etc. Traditional methods using complex models and look-up tables have high computation requirements which makes them unsuitable for online applications. In this paper, we propose a simple method for simultaneous SOC, Qmax and internal resistance estimation based on a second-order equivalent circuit model (ECM). A Variable Model framework based Adaptive Extended Kalman filter (VM-AEKF) is implemented for joint SOC and model parameter estimation where the VM framework is designed specifically to improve the stability and accuracy of parameter estimation under conditions when the system is not sufficiently excited by the input signal. Simultaneously, a…
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Improving battery safety and longevity through uncertainty modeling of lithium-ion batteries and preventing the local over-charge/over-discharge

Trine University-Changhong Liu
  • Technical Paper
  • 2020-01-0450
To be published on 2020-04-14 by SAE International in United States
The battery electrodes are porous and have complicated microstructures due to irregular sizes and shapes of pores. Electrode design parameters like porosity, thickness, particle size, and conductivity can vary from one local area to another in one cell. Even under the normal operating range, some local areas may experience over-charge/over-discharge, extensive degradation, and rapid heat generation. These local events are not easy to observe or measure at the beginning and can eventually lead to catastrophic failure of the whole cell if no actions are taken. Therefore, the uncertainty of these parameters has a significant effect on the longevity and safety of batteries. Most of the electrochemical battery models assume design parameters have constant values in a cell which is not able to capture the uncertainty described above. To prevent any catastrophic failure, the applied current should be cut off before any over-charge/over-discharge and rapid heat generation caused by these random local areas. In this work, a new method is developed to simulate random local events and design new control strategies to increase longevity and safety.…
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Battery Entropic Heating Coefficient Testing and Use in Cell-level Loss Modeling for Extreme Fast Charging

FCA US LLC-Pawel Malysz, Oliver Gross
McMaster Automotive Resource Centre-Jeremy Lempert, Phillip Kollmeyer, Ali Emadi
  • Technical Paper
  • 2020-01-0862
To be published on 2020-04-14 by SAE International in United States
To achieve an accurate estimate of losses in a battery it is necessary to consider the reversible entropic losses, which may constitute over 20% of the peak total loss. In this work, a procedure for experimentally determining the entropic heating coefficient of a lithium-ion battery cell is developed. The entropic heating coefficient is the rate of change of the cell’s open-circuit voltage (OCV) with respect to temperature; it is a function of state-of-charge (SOC) and temperature and is often expressed in mV/K. The reversible losses inside the cell are a function of the current, the temperature, and the entropic heating coefficient, which itself is dependent on the cell chemistry. The total cell losses are the sum of the reversible and irreversible losses, where the irreversible losses consist of ohmic losses in the electrodes, ion transport losses, and other irreversible chemical reactions. The entropic heating coefficient is determined by exposing the cell to a range of temperatures at each SOC value of interest. The OCV is recorded at each combination of SOC and temperature, and ∂OCV/∂T…
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Proposed Standards and Methods for Leak Testing Lithium-Ion Batteries with Empirically Derived Rejection Limits

Inficon GmbH-Daniel Wetzig, Maximillian Reismann
  • Technical Paper
  • 2020-01-0448
To be published on 2020-04-14 by SAE International in United States
Lithium-ion batteries are a highly suitable energy source for many applications, particularly in the automotive sector due to their high energy density and low self-discharge rate. During the production of battery cells, rapid detection of leaks is absolutely essential to achieve necessary lifetime and safety requirements. This applies particularly to small leaks that cannot be detected electrically immediately after the cell has been manufactured. Remarkably, for pouch cells there has been no reliable method available to detect small leak channels. This paper examines a spectrum of leak scenarios for cylindrical, prismatic and pouch lithium-ion batteries. Rejection limits for lithium-ion batteries have not been codified. Fact-based rejection limits now have been empirically established. This presentation will discuss how small leaks—down to the 10e-6 mbar l/s range—can be detected reliably and quantitatively on potentially leaking battery cells through detection of escaping liquid electrolyte vapors, typically DMC (dimethyl carbonate). The test system is applicable to non-rigid pouch cells and rigid prismatic or cylindrical cells, which permits non-destructive testing of any lithium-ion battery cell.
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Calibration of Electrochemical Models for Li-ion Battery Cells using Three-Electrode Testing

Ford Motor Company-Chulheung Bae, Jie Deng
SK Innovation-Heechan Park
  • Technical Paper
  • 2020-01-1184
To be published on 2020-04-14 by SAE International in United States
Electrochemical models of Lithium ion batteries are today a standard tool in the automotive industry for activities related to the computer-aided design, analysis, and optimization of energy storage systems for electrified vehicles. One of the challenges in the development or use of such models is the need of detailed information on the cell and electrode geometry or properties of the electrode and electrolyte materials, which are typically unavailable or difficult to retrieve by end-users. This forces engineers to resort to “hand-tuning” of many physical and geometrical parameters, using standard cell-level characterization tests. This paper proposes a method to provide information and data on individual electrode performance that can be used to simplify the calibration process for electrochemical models. The proposed approach consists in inserting a reference electrode in a commercial Li-ion cell to obtain real-time data of how the cathode and anode interact with one another during cell operation, rather than resorting to coin cell testing of individual electrode materials. The paper will illustrate the technique developed for the reference electrode insertion, then describe the…
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Bench-marking Computational Performance of Dynamic Programming For Speed Profiling and Fuel Efficiency of Autonomous-capable HEV

Ohio State University-Wilson Perez, Amit Ruhela, Punit Tulpule
  • Technical Paper
  • 2020-01-0968
To be published on 2020-04-14 by SAE International in United States
Dynamic programming has been used for optimal control of hybrid powertrain and vehicle speed optimization particularly in design phase for over a couple of decades. With the advent of autonomous and connected vehicle technologies, automotive industry is getting closer to implementing predictive optimal control strategies in real time applications. The biggest challenge in implementation of optimal controls is the limitation on hardware which includes processor speed, IO speed, and random access memory. Due to the use of autonomous features, modern vehicles are equipped with better onboard computational resources. In this paper we present a comparison between multiple hardware options for dynamic programming. The optimal control problem considered, is the optimization of travel time and fuel economy by tuning the torque split ratio and vehicle speed while maintaining charge sustaining operation. The system has two states - battery state of charge and vehicle speed, and two inputs namely, total torque and torque split ratio. First, we develop a Matlab® based program to solve the optimal control problem. The Matlab® code is optimized for performance and memory…