Dynamical modeling procedure of a Li-ion battery pack suitable for real-time applications

2015 ◽  
Vol 92 ◽  
pp. 396-405 ◽  
Author(s):  
S. Castano ◽  
L. Gauchia ◽  
E. Voncila ◽  
J. Sanz
Keyword(s):  
Real Time ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Dynamical Modeling ◽  
Modeling Procedure ◽  
Li Ion ◽  
Real Time Applications

Real Time Prediction of Li-Ion Battery Pack Temperatures in EV Vehicles

2020 ◽  
Author(s):  
Azita Soleymani ◽  
William Maltz
Keyword(s):  
Real Time ◽  
Heat Generation ◽  
Equivalent Circuit Model ◽  
Battery Pack ◽  
Generation Rate ◽  
Li Ion Battery ◽  
Heat Generation Rate ◽  
Digital Twin ◽  
Twin Model ◽  
Li Ion

Abstract A semi-analytical digital twin model of a 90 kW.h li-ion battery pack was developed to capture thermal behavior of the pack in a real-time environment. The solution uses reduced-order models that minimize compute cost/time yet are accurate in predicting real-world operation. The real-time heat generation rate in the battery pack is calculated using 2RC equivalent circuit model. A series of HPPC tests were conducted to calibrate the equivalent circuit model in order to accurately calculate heat generation rate as a function of SOC, temperature, current, charge/discharge mode and pulse duration. In the paper, live-sensor data was integrated into the digital twin system level model of the battery pack to create a real-time environment. The generated tool was utilized to monitor the real-time temperature of the battery pack remotely and have a predictive maintenance solution. The model results for heat generation rate, terminal voltage, and temperature were found to be consistent with the test data across a wide range of conditions. The generated model was used to accelerate battery pack design and development by enabling the evaluation of design feasibility and to conduct in-depth root causes analyses for various inputs and operating conditions, including initial SOC, temperature, coolant flow rate, different charge and discharge profiles. The resulting digital twin model provides additional data that cannot be measured offering the EV industry an opportunity to improve its safety record.

Development of a Two-Dimensional Thermal Model for Li-Ion Battery Pack With Experimental Validation

2019 ◽  
Vol 12 (2) ◽  
Author(s):  
Haoting Wang ◽  
Ning Liu ◽  
Lin Ma
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Experimental Validation ◽  
Computational Cost ◽  
Battery Pack ◽  
Two Dimensional ◽  
Li Ion Battery ◽  
New Approach ◽  
Battery Packs ◽  
Li Ion

Abstract This paper reports the development of a two-dimensional two states (2D2S) model for the analysis of thermal behaviors of Li-ion battery packs and its experimental validation. This development was motivated by the need to fill a niche in our current modeling capabilities: the need to analyze 2D temperature (T) distributions in large-scale battery packs in real time. Past models were predominately developed to either provide detailed T information with high computational cost or provide real-time analysis but only 1D lumped T information. However, the capability to model 2D T field in real time is desirable in many applications ranging from the optimal design of cooling strategies to onboard monitoring and control. Therefore, this work developed a new approach to provide this desired capability. The key innovations in our new approach involved modeling the whole battery pack as a complete thermal-fluid network and at the same time calculating only two states (surface and core T) for each cell. Modeling the whole pack as a complete network captured the interactions between cells and enabled the accurate resolution of the 2D T distribution. Limiting the calculation to only the surface and core T controlled the computational cost at a manageable level and rendered the model suitable for packs at large scale with many cells.

Current-Split Estimation in Li-Ion Battery Pack: An Enhanced Weighted Recursive Filter Method

2015 ◽  
Vol 1 (4) ◽  
pp. 402-412 ◽  
Author(s):  
Haris M. Khalid ◽  
Qadeer Ahmed ◽  
Jimmy C.-H. Peng ◽  
Giorgio Rizzoni
Keyword(s):  
Battery Pack ◽  
Filter Method ◽  
Li Ion Battery ◽  
Recursive Filter ◽  
Li Ion

Real-Time Estimation of Lithium-Ion Concentration in Both Electrodes of a Lithium-Ion Battery Cell Utilizing Electrochemical–Thermal Coupling

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Satadru Dey ◽  
Beshah Ayalew
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Time Estimation ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Thermal Dynamics ◽  
Estimation Scheme ◽  
Real Time Estimation ◽  
Li Ion

This paper proposes and demonstrates an estimation scheme for Li-ion concentrations in both electrodes of a Li-ion battery cell. The well-known observability deficiencies in the two-electrode electrochemical models of Li-ion battery cells are first overcome by extending them with a thermal evolution model. Essentially, coupling of electrochemical–thermal dynamics emerging from the fact that the lithium concentrations contribute to the entropic heat generation is utilized to overcome the observability issue. Then, an estimation scheme comprised of a cascade of a sliding-mode observer and an unscented Kalman filter (UKF) is constructed that exploits the resulting structure of the coupled model. The approach gives new real-time estimation capabilities for two often-sought pieces of information about a battery cell: (1) estimation of cell-capacity and (2) tracking the capacity loss due to degradation mechanisms such as lithium plating. These capabilities are possible since the two-electrode model needs not be reduced further to a single-electrode model by adding Li conservation assumptions, which do not hold with long-term operation. Simulation studies are included for the validation of the proposed scheme. Effect of measurement noise and parametric uncertainties is also included in the simulation results to evaluate the performance of the proposed scheme.

A Methodological Approach for Supporting the Thermal Design of Li-Ion Battery for Customized Electric Vehicles

2014 ◽  
Author(s):  
Daniele Landi ◽  
Paolo Cicconi ◽  
Michele Germani
Keyword(s):  
Thermal Behavior ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Thermal Design ◽  
Battery Pack ◽  
Scale Production ◽  
Li Ion Battery ◽  
Suitable Alternative ◽  
Li Ion

An important issue in the mechanical industry is the reduction of the time to market, in order to meet quickly the customer needs. This goal is very important for SMEs that produce small lots of customized products. In the context of greenhouse gas emissions reduction, vehicles powered by electric motors seem to be the most suitable alternative to the traditional internal combustion engine vehicles. The market of customized electric vehicles is a niche market suitable for SMEs. Nowadays, the energy storage system of an electric vehicle powertrain consists of several Li-ion cells arranged in a container called battery pack. Particularly, the battery unit is considered as the most critical component in electric vehicle, because it impacts on performance and life cycle cost. Currently, the design of a battery pack mostly depends on the related market size. A longer design time is expected in the case of a large scale production. While a small customized production requires more agility and velocity in the design process. The proposed research focuses on a design methodology to support the designer in the evaluation of the battery thermal behavior. This work has been applied in the context of a customized small production. As test case, an urban electric light commercial vehicle has been analyzed. The designed battery layout has been evaluated and simulated using virtual prototyping tools. A cooling configuration has been analyzed and then prototyped in a physical vehicle. The virtual thermal behavior of a Li-ion battery has been validated at the test bench. The real operational conditions have been analyzed reproducing several ECE-15 driving cycles and many acceleration runs at different load values. Thermocouples have measured the temperature values during the physical experiments, in order to validate the analytical thermal profile evaluated with the proposed design approach.

scholarly journals Reliability Analysis of Different Cell Configurations of Lithium ion battery Pack

2019 ◽  
Vol 18 (2) ◽  
pp. 49-56
Author(s):  
Md. Nahian Al Subri Ivan ◽  
Sujit Devnath ◽  
Rethwan Faiz ◽  
Kazi Firoz Ahmed
Keyword(s):  
Mathematical Model ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Series Configuration ◽  
Li Ion ◽  
Parallel Module ◽  
The Mathematical Model ◽  
Parallel Series

To infer and predict the reliability of the remaining useful life of a lithium-ion (Li-ion) battery is very significant in the sectors associated with power source proficiency. As an energy source of electric vehicles (EV), Li-ion battery is getting attention due to its lighter weight and capability of storing higher energy. Problems with the reliability arises while li-ion batteries of higher voltages are required. As in this case several li-ion cells areconnected in series and failure of one cell may cause the failure of the whole battery pack. In this paper, Firstly, the capacity degradation of li-ion cells after each cycle is observed and secondly with the help of MATLAB 2016 a mathematical model is developed using Weibull Probability Distribution and Exponential Distribution to find the reliability of different types of cell configurations of a non-redundant li-ion battery pack. The mathematical model shows that the parallel-series configuration of cells is more reliable than the series configuration of cells. The mathematical model also shows that if the discharge rate (C-rate) remains constant; there could be an optimum number for increasing the cells in the parallel module of a parallel-series onfiguration of cells of a non-redundant li-ion battery pack; after which only increasing the number of cells in parallel module doesn’t increase the reliability of the whole battery pack significantly. 

scholarly journals Real Time Observation of Nanomaterials in Energy Harvesting and Li-ion Battery Systems

2011 ◽  
Vol 17 (S2) ◽  
pp. 1570-1571
Author(s):  
R Shahbazian-Yassar ◽  
H Ghassemi ◽  
A Asthana ◽  
M Au ◽  
Y Yap
Keyword(s):  
Energy Harvesting ◽  
Real Time ◽  
Li Ion Battery ◽  
Battery Systems ◽  
Li Ion ◽  
Time Observation ◽  
Real Time Observation

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011.

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