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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Serie: Automotive Series
- Sprache: Englisch
- Veröffentlichungsjahr: 2017
Thermal Management of Electric Vehicle Battery Systems provides a thorough examination of various conventional and cutting edge electric vehicle (EV) battery thermal management systems (including phase change material) that are currently used in the industry as well as being proposed for future EV batteries. It covers how to select the right thermal management design, configuration and parameters for the users' battery chemistry, applications and operating conditions, and provides guidance on the setup, instrumentation and operation of their thermal management systems (TMS) in the most efficient and effective manner. This book provides the reader with the necessary information to develop a capable battery TMS that can keep the cells operating within the ideal operating temperature ranges and uniformities, while minimizing the associated energy consumption, cost and environmental impact. The procedures used are explained step-by-step, and generic and widely used parameters are utilized as much as possible to enable the reader to incorporate the conducted analyses to the systems they are working on. Also included are comprehensive thermodynamic modelling and analyses of TMSs as well as databanks of component costs and environmental impacts, which can be useful for providing new ideas on improving vehicle designs. Key features: * Discusses traditional and cutting edge technologies as well as research directions * Covers thermal management systems and their selection for different vehicles and applications * Includes case studies and practical examples from the industry * Covers thermodynamic analyses and assessment methods, including those based on energy and exergy, as well as exergoeconomic, exergoenvironmental and enviroeconomic techniques * Accompanied by a website hosting codes, models, and economic and environmental databases as well as various related information Thermal Management of Electric Vehicle Battery Systems is a unique book on electric vehicle thermal management systems for researchers and practitioners in industry, and is also a suitable textbook for senior-level undergraduate and graduate courses.
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Table of Contents
Cover
Title Page
Copyright
Preface
Acknowledgements
Chapter 1: Introductory Aspects of Electric Vehicles
1.1 Introduction
1.2 Technology Development and Commercialization
1.3 Vehicle Configurations
1.4 Hybridization Rate
1.5 Vehicle Architecture
1.6 Energy Storage System
1.7 Grid Connection
1.8 Sustainability, Environmental Impact and Cost Aspects
1.9 Vehicle Thermal Management
1.10 Vehicle Drive Patterns and Cycles
1.11 Case Study
1.12 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Chapter 2: Electric Vehicle Battery Technologies
2.1 Introduction
2.2 Current Battery Technologies
2.3 Battery Technologies under Development
2.4 Battery Characteristics
2.5 Battery Management Systems
2.6 Battery Manufacturing and Testing Processes
2.7 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Chapter 3: Phase Change Materials for Passive TMSs
3.1 Introduction
3.2 Basic Properties and Types of PCMs
3.5 Cost and Environmental Impact of Phase Change Materials
3.6 Applications of PCMs
3.7 Case Study I: Heat Exchanger Design and Optimization Model for EV Batteries using PCMs
3.8 Case Study 2: Melting and Solidification of Paraffin in a Spherical Shell from Forced External Convection
3.9 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Chapter 4: Simulation and Experimental Investigation of Battery TMSs
4.1 Introduction
4.2 Numerical Model Development for Cell and Submodules
4.3 Cell and Module Level Experimentation Set Up and Procedure
4.4 Vehicle Level Experimentation Set Up and Procedure
4.5 Illustrative Example: Simulations and Experimentations on the Liquid Battery Thermal Management System Using PCMs
4.6 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Chapter 5: Energy and Exergy Analyses of Battery TMSs
5.1 Introduction
5.2 TMS Comparison
5.3 Modeling of Major TMS Components
5.4 Energy and Exergy Analyses
5.5 Illustrative Example: Liquid Battery Thermal Management Systems
5.6 Case Study: Transcritical CO
2
-Based Electric Vehicle BTMS
5.7 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Chapter 6: Cost, Environmental Impact and Multi-Objective Optimization of Battery TMSs
6.1 Introduction
6.2 Exergoeconomic Analysis
6.3 Exergoenvironmental Analysis
6.4 Optimization Methodology
6.5 Illustrative Example: Liquid Battery Thermal Management Systems
6.6 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Chapter 7: Case Studies
7.1 Introduction
7.2 Case Study 1: Economic and Environmental Comparison of Conventional, Hybrid, Electric and Hydrogen Fuel Cell Vehicles
7.3 Case Study 2: Experimental and Theoretical Investigation of Temperature Distributions in a Prismatic Lithium-Ion Battery
7.4 Case Study 3: Thermal Management Solutions for Electric Vehicle Lithium-Ion Batteries based on Vehicle Charge and Discharge Cycles
7.5 Case Study 4: Heat Transfer and Thermal Management of Electric Vehicle Batteries with Phase Change Materials
7.6 Case Study 5: Experimental and Theoretical Investigation of Novel Phase Change Materials For Thermal Applications
Nomenclature
References
Chapter 8: Alternative Dimensions and Future Expectations
8.1 Introduction
8.2 Outstanding Challenges
8.3 Emerging EV Technologies and Trends
8.4 Future BTM Technologies
8.5 Concluding Remarks
Nomenclature
Study Questions/Problems
References
Index
End User License Agreement
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Guide
cover
Table of Contents
Preface
Begin Reading
List of Illustrations
Chapter 1: Introductory Aspects of Electric Vehicles
Figure 1.1 Illustration of internal combustion engine vehicle configuration.
Figure 1.2 Illustration of the electric vehicle configuration.
Figure 1.3 Illustrations of (a) hybrid and (b) plug-in hybrid electric vehicle configurations.
Figure 1.4 Conceptual illustration of battery discharge.
Figure 1.5 The factors influencing the market penetration of various technologies (adapted from Dijk
et al
., 2013).
Figure 1.6 Fit-stretch pattern for different powertrain technologies (adapted from Hoogma, 2000).
Figure 1.7 Sodium borohyride fuel cell vehicle (courtesy of TUBITAK Marmara Research Center).
Figure 1.8 Hybrid classification based on powertrain functionality (adapted from Karden
et al
., 2007).
Figure 1.9 Hybrid vehicles configurations in (a) series, (b) parallel and (c) series/parallel.
Figure 1.10 Images and schematics of a common battery (courtesy of TUBITAK Marmara Research Center).
Figure 1.11 Comparison of the power versus energy density characteristics of various ESSs (adapted from Guerrero
et al
., 2010).
Figure 1.12 Illustrations of powerpacks using ultracapacitors with VRLA and li-ion batteries, respectively (courtesy of TUBITAK Marmara Research Center).
Figure 1.13 A basic configuration of a proton exchange membrane fuel cell.
Figure 1.14 Level 3 charging station concept.
Figure 1.15 Illustration of the inductive charging technology.
Figure 1.16 Illustration of smart grid operation.
Figure 1.17 A conceptual representation of integrating renewable energy into a smart grid system.
Figure 1.18 Life-cycle GHG emissions sensitivity of CVs, HEVs, PHEV30 and PHEV90 under different carbon intensity scenarios (data from Samaras and Meisterling, 2008).
Figure 1.19 Simplified radiator circuit of a HEV (adapted from WopOnTour, 2010).
Figure 1.20 Simplified power electronics cooling circuit of a HEV (adapted from WopOnTour, 2010).
Figure 1.21 Simplified drive unit circuit of a HEV.
Figure 1.22 Simplified A/C circuit of a HEV (adapted from WopOnTour, 2010).
Figure 1.23 Vehicle performance testing using a preloaded drive cycle (courtesy of TUBITAK Marmara Research Center).
Figure 1.24 Total vehicle fleet according to the vehicle types between 2005 and 2013 (data from road motor vehicle statistics report, 2013).
Figure 1.25 Market share percentages for electrified vehicle compared to all vehicles in 2013 (data from ABB, 2014).
Figure 1.26 Gasoline prices as of 07, july 2014 (data from GlobalPetrolPrices, 2014).
Chapter 2: Electric Vehicle Battery Technologies
Figure 2.1 Representation of battery technology to be utilized in various applications
Figure 2.2 Typical lead-acid battery.
Figure 2.3 A NiMH battery cell and pack
Figure 2.4 Sample pouch type lithium-ion battery
Figure 2.5 Practical specific energies of some of the most commonly used and researched rechargeable batteries for EV applications (adapted from Bruce
et al
., 2012).
Figure 2.6 Typical PHEV cell cost structure (adapted from Roland Berger, 2012).
Figure 2.7 Typical battery package and associated power electronics cost for EV (adapted from Pillot, 2013).
Figure 2.8 Energy consumption (cradle-to-grave) and average CO
2
emissions associated with typical EV battery chemistries (adapted from Argonne National Laboratory, 2010).
Figure 2.9 Environmental impact of the evaluated technologies based on Eco-indicator 99 (adapted from Bossche
et al
., 2006).
Figure 2.10 Processing plant at galaxy lithium mine in Ravensthorpe, Western Australia.
Figure 2.11 Lead-acid batteries waiting to be recycled.
Figure 2.12 Average historical minimum and maximum temperatures in Ontario, Canada (adapted from Climatemps, 2014).
Figure 2.13 Configuration of a typical battery management system (adapted from Xing
et al
., 2011).
Figure 2.14 Battery size and operating characteristic of various electric vehicle configurations (adapted from Chrysler Group LLC, 2012).
Figure 2.15 Qualitative dependency of SOF on SOC and SOH at a given temperature (adapted from Meissner and Richter, 2003).
Figure 2.16 Battery voltage and current during recharge (adapted from A123, 2013).
Figure 2.17 Hierarchical structure of a typical BMS (adapted from Brandl
et al
., 2012).
Figure 2.18 The effects of charge imbalance on all-electric vehicle range (adapted from Honda, 2015).
Figure 2.19 Production of typical pouch Lithium-ion cells
Figure 2.20 Conventional cell production methodology for Li-ion pouch cells
Figure 2.21 Typical battery pack diagram for EV applications (adapted from ISO 12405–2, 2012).
Figure 2.22 Typical cell/module testing equipment
Chapter 3: Phase Change Materials for Passive TMSs
Figure 3.1 The heat storage capacities (sensible versus latent) of various materials.
Figure 3.2 Different types of phase change materials (courtesy of PCM Products).
Figure 3.3 Types of solid-liquid phase change materials.
Figure 3.4 Melting temperature and phase change enthalpy for existing PCMs (adapted from Dieckmann, 2006).
Figure 3.5 Temperature ranges and associated enthalpy of fusion of various PCMs that can be used in EV BTMS applications (adapted from Troxtechnik, 2015).
Figure 3.6 Picture of an organic PCM (courtesy of Rubitherm GmbH).
Figure 3.7 Picture of an inorganic PCM (courtesy of Rubitherm GmbH).
Figure 3.8 Picture of a microencapsulation of PCMs (courtesy of Rubitherm GmbH).
Figure 3.9 Most common types of organic PCMs used in TES applications (courtesy of PCM Products).
Figure 3.10 PCMs used in electrical equipment and chilled water cooling application (courtesy of PCM Products).
Figure 3.11 Example of various PCMs used for battery applications (courtesy of PCM Products).
Figure 3.12 Simplified schematics of the analyzed HEV TMS.
Figure 3.13 Physical model of heat exchanger.
Figure 3.14 Effect of CNT concentration on the thermal conductivity of the mixture in parallel configuration.
Figure 3.15 Thermal conductivity of the PCM and nanoparticles in series arrangement.
Figure 3.16 Thermal conductivity as a function of concentration and probability.
Figure 3.17 Variation on length of heat exchanger versus effective thermal conductivity of the PCM.
Figure 3.18 Variation of optimum shell (tank) diameter versus tube outside diameter in the case of without fin.
Figure 3.19 Variation of optimum tube length versus tube inside diameter in the case of without fin.
Figure 3.20 Variation of L/di and D/do with tube index.
Figure 3.21 Variation of optimum value of tube length versus tube inner diameter for various rate of heat transfer.
Figure 3.22 Dependency of Re, rate of heat transfer and L/d for various tube diameter.
Figure 3.23 Variation of heat exchanger length with the probability of CNT in series configuration and concentration.
Figure 3.24 Contour of heat exchanger length versus CNT series probability and CNT concentration.
Figure 3.25 Experimental apparatus used for the charging and discharging of the latent store using a forced air flow, modified from Ettouney
et al.
(2005).
Figure 3.26 Wall grid volumes for the computational domain considered for a latent TES. The PCM capsule volumes are shown in the darker center region (adapted from Dincer and Rosen, 2010).
Figure 3.27 Comparison of numerical temperature profiles at three locations in the sphere with the experimental results from Ettouney
et. al.
(2005), for the model validation (adapted from Dincer and Rosen, 2010).
Figure 3.28 Liquid fraction as a function of time for the grid size independence tests for the sphere (adapted from Dincer and Rosen, (2010).
Figure 3.29 Liquid fraction as a function of time for the time step independence tests for the sphere (adapted from Dincer and Rosen, 2010).
Figure 3.30 Variation of liquid fraction for the charging and discharging cases with dimensionless time
t
*, for several inlet air temperatures (adapted from Dincer and Rosen, 2010).
Figure 3.31 Variation of the energy stored and the heat generated through viscous dissipation for the two charging cases, as represented by the two inlet air temperatures considered (adapted from Dincer and Rosen, 2010).
Figure 3.32 Variation of the energy recovered and the heat generated through viscous dissipation for the two discharging cases, as represented by the two inlet air temperatures considered (adapted from Dincer and Rosen, 2010).
Figure 3.33 Variation of energy and exergy efficiencies with dimensionless time
t
* for the charging process, for two inlet air temperatures (adapted from Dincer and Rosen, 2010).
Figure 3.34 Variation of energy and exergy efficiencies with dimensionless time
t
* for the discharging process, for two inlet air temperatures (adapted from Dincer and Rosen, 2010).
Figure 3.35 Variation with dimensionless time
t
* of exergy stored, destroyed via viscous dissipation and destroyed via heat transfer during charging, for two inlet air temperatures (adapted from Dincer and Rosen, 2010).
Figure 3.36 Variation with dimensionless time
t
* of exergy recovered, destroyed via viscous dissipation and destroyed via heat transfer during discharging, for two inlet air temperatures (adapted from Dincer and Rosen, 2010).
Figure 3.37 Exergy destroyed via viscous dissipation and heat transfer, and the total exergy destruction, after the overall storage process, for all inlet air temperature cases (adapted from Dincer and Rosen, 2010).
Figure 3.38 Energy and exergy efficiencies at the completion of the overall storage process, for all inlet air temperature cases (adapted from Dincer and Rosen, 2010).
Chapter 4: Simulation and Experimental Investigation of Battery TMSs
Figure 4.1 Relationship single cell model in the submodule.
Figure 4.2 Physical domain for the submodule.
Figure 4.3 Boundary conditions for a sample Li-Ion cell.
Figure 4.4 Chebyshev polynomial to interpolate specific heat.
Figure 4.5 Representation of superposition rule for our system.
Figure 4.6 Connecting thermocouples on the surface of the Li-Ion cells.
Figure 4.8 Submodule with three cells under the tests performed in Dr. Greg Rohrauer's Lab.
Figure 4.9 Foams after soaking in the PCM to assess their absorption.
Figure 4.10 Position of thermocouples in equal distances from the copper tube.
Figure 4.11 Position of thermocouples on the tube surface.
Figure 4.12 Manufactured heat exchanger with optimized dimensions.
Figure 4.13 Solid phase of the PCM in the heat exchanger and test set up.
Figure 4.14 Preparation of samples using ultrasonic unit in Dr. Greg Rohrauer's Lab.
Figure 4.15 The developed stainless steel micro-mesh with mesh size of 20 µm.
Figure 4.16 Schematic of the test bench refrigerant loop used.
Figure 4.17 Schematic of the experimental set up.
Figure 4.18 Application of data acquisition software in the vehicle (modified from IPETRONIK, 2009).
Figure 4.19 Data acquisition system installed in the trunk of an electric vehicle.
Figure 4.20 Sensors used in the data acquisition system.
Figure 4.21 A commonly utilized flow transceiver used in the experimentations.
Figure 4.22 Sample screenshot from the data manager main navigation screen.
Figure 4.23 Experimental set up of the electric vehicle thermal management system.
Figure 4.24 Schematic of cell and surrounding PCM.
Figure 4.25 Grid independence investigation of the cell with PCM.
Figure 4.26 Temperature contours in cell without the application of PCMs.
Figure 4.27 Temperature distribution along the horizontal rakes.
Figure 4.28 Temperature distribution along (a) the vertical rake for the single cell and (b) the critical rake compared to the bottom rake.
Figure 4.29 Time step independence study of the mesh.
Figure 4.30 (a) Location of vertical and critical rakes in cell and (b) temperature contours in the cell with PCM (3 mm) around cell.
Figure 4.31 The change in the location of maximum temperature point in the vertical rake in cell.
Figure 4.32 Transient response of the cell without PCM and with 3 mm thickness PCM.
Figure 4.33 Effect of the PCM in preventing a temperature increase in the cell.
Figure 4.34 Temperature contours in the cell surrounded by 9 mm thick PCM.
Figure 4.35 Steady-state temperature distributions along the vertical rake in cell.
Figure 4.36 Temperature distribution in the horizontal rake after 20 minutes.
Figure 4.37 Temperature distribution along the horizontal rake in the cell after 20 minutes.
Figure 4.38 Transient response for maximum cell temperature for different thicknesses.
Figure 4.39 Average cell temperature with different PCM thicknesses after 20 minutes.
Figure 4.40 Cooling effectiveness for different PCM thicknesses.
Figure 4.41 Overall temperature coefficients along the horizontal rake in the cell for different PCM thicknesses.
Figure 4.42 Li-Ion cell, cooling fin and foam mesh.
Figure 4.43 Temperature comparison in vertical direction in second cell with and without PCM.
Figure 4.44 Location of points on the cell surface and the rake through submodule.
Figure 4.45 Effect of PCM on temperature increase on the cell surface.
Figure 4.46 Temperature distribution along the thickness of the submodule after 50 minutes.
Figure 4.47 Effect of PCM on cell temperature increase (under a heat-generating rate of 63.97 kW/m
3
).
Figure 4.48 Temperature difference in submodule thickness with and without PCM under a heat generation rate of 63.97 kW/m
3
.
Figure 4.49 Configuration of cells, PCM sheets and cooling plates in the submodule with the monitoring line location on the right.
Figure 4.50 Temperature contours in the submodule (a) without PCM and (b) with PCM.
Figure 4.51 Temperature distribution in cell 2 height.
Figure 4.52 Comparison of temperature distribution along submodule thickness.
Figure 4.53 Temperature distribution along the critical height in submodule with and without PCM.
Figure 4.54 Transient response of submodule in different time steps.
Figure 4.55 The effect of PCM in the temperature of middle cell in the submodule.
Figure 4.56 Time-dependent temperature behavior of the middle cell in the submodule.
Figure 4.57 Transient melting behavior of PCM around submodule.
Figure 4.58 Quasi steady-state temperature dependence of submodule for heat generation of 22,800 W/m
3
.
Figure 4.59 Temperature along submodule thickness for different volumetric heat generation rates.
Figure 4.60 Temperature increase in mid-cell under various heat generation rates.
Figure 4.61 Submodule response for the higher heat generation rate in battery pack (200 kW/m
3
).
Figure 4.62 Location of thermocouples on the surface of Li-Ion cells.
Figure 4.63 Temperature variations for all 10 points on both sides of the cell with and without the PCM.
Figure 4.64 Experimentally measured cell temperature with and without PCM in between the cells.
Figure 4.65 Differential scanning calorimetry results for pure n-octadecan (99%) in heating and cooling periods.
Figure 4.66 Differential scanning calorimetry results for technical grade octadecane (90.8%).
Figure 4.67 DSC test results for mixture of 6% mass concentration of cnt and 99% (pure) PCM.
Figure 4.68 DSC test results for the mixture of 6% graphene platelets mixed with technical-grade PCM.
Figure 4.69 Ratio of effective thermal conductivity of 99% CNT to technical grade (90.8%) octadecane.
Figure 4.70 Comparing CNT and platelets of graphene-effective thermal conductivity.
Figure 4.71 Temperature in locations 1, 2 and 3 in the case of pure PCM.
Figure 4.72 Temperature increase in the pure PCM compared to the inlet temperature.
Figure 4.73 Optical image of pure PCM.
Figure 4.74 Structure of technical-grade PCM with x500 magnification using optical microscope.
Figure 4.75 Optical image of 1.25% CNT and pure PCM mixture.
Figure 4.76 (a) Optical image of 3% CNT and pure PCM mixture and (b) graphene platelets with 1.25% mass fraction mixed with technical PCM.
Figure 4.77 Optical image of 6% CNT and pure PCM mixture.
Figure 4.78 Transmission optical image of the 1.25% CNT and pure PCM mixture.
Figure 4.79 Transmission optical image of 6% CNT and pure PCM mixture.
Figure 4.80 Effect of metal micro-mesh on agglomeration of nano-particles.
Figure 4.81 Refrigerant temperature before and after the compressor.
Figure 4.90 Compressor electric power.
Figure 4.91 Refrigerant temperature before and after the compressor.
Figure 4.106 RESS temperature.
Chapter 5: Energy and Exergy Analyses of Battery TMSs
Figure 5.1 General schematic diagram of cabin air TMS.
Figure 5.2 General schematic of refrigerant-based TMS.
Figure 5.3 General schematic of liquid-based TMS (A: bypass route, B: battery cooler route, C: chiller route).
Figure 5.4 Temperature rise in the battery with time based on natural convection and various thermal management systems.
Figure 5.5 Simplified representation of the hybrid electric vehicle thermal management system.
Figure 5.6 Baseline model (a) exergy efficiency and (b) exergy destruction rate of each component in the refrigerant and coolant cycles.
Figure 5.7 Compression ratio with respect to (a) evaporating and (b) condensing temperatures.
Figure 5.8 Cooling load with respect to (a) Evaporating and (b) Condensing temperatures.
Figure 5.9 Energetic COP with respect to (a) Evaporating and (b) Condensing temperatures.
Figure 5.10 Exergetic COP with respect to (a) Evaporating and (b) Condensing temperatures.
Figure 5.11 Exergy destruction rate with respect to (a) Evaporating and (b) Condensing temperatures.
Figure 5.12 (a) Exergetic COP and (b) Exergy destruction rate with respect to superheating temperatures.
Figure 5.13 (a) Exergetic COP and (b) Exergy destruction rate with respect to subcooling temperatures.
Figure 5.14 Pressure drop with respect to (a) Evaporator and (b) Condenser air mass flow rates.
Figure 5.15 (a) Exergetic COP and (b) Exergy destruction rate with respect to evaporator pressure drop.
Figure 5.16 (a) Exergetic COP and (b) Exergy destruction rate with respect to compression ratio.
Figure 5.17 Liquid saturation temperature versus pressure for various refrigerants.
Figure 5.18 Compression ratio of the TMS with respect to (a) Evaporating and (b) Condensing temperatures using various refrigerants.
Figure 5.20 Refrigerant mass flow rate with respect to (a) Evaporating and (b) Condensing temperatures using various refrigerants.
Figure 5.21 Energetic COP of the TMS with respect to (a) Evaporating and (b) Condensing temperatures using various refrigerants.
Figure 5.23 Exergy destruction of the TMS with respect to (a) Evaporating and (b) Condensing temperatures using various refrigerants.
Figure 5.24 (a) GHG Emissions and sustainability index with respect to baseline TMS exergetic COPs (b) Under various carbon intensity of electricity generation.
Figure 5.25 (a) GHG emissions and (b) Sustainability index with respect to exergetic COPs of the TMSs using various refrigerants.
Figure 5.26 Normalized exergy destruction values associated with the compressor based on the conducted enhanced exergy analysis.
Figure 5.32 Normalized exergy destruction values associated with the battery based on the conducted enhanced exergy analysis.
Figure 5.33 Representation of the studied basic EV BTMS system using carbon dioxide and 50–50 water/glycol mix.
Figure 5.34 Representation of the EV BTMS with two-stage compression, intercooler and internal heat exchanger, using carbon dioxide and 50–50 water/glycol mix.
Figure 5.35 Vapour pressure for R744 and the compared refrigerants.
Figure 5.36 Slope of saturation pressure curve for R744 and the compared refrigerants.
Figure 5.37 Compressor work of different EV BTMSs using carbon dioxide as refrigerant under varying evaporating temperatures.
Figure 5.40 Exergy destruction of different EV BTMSs using carbon dioxide as refrigerant under varying evaporating temperatures.
Figure 5.41 Exergy efficiency of each component in the two-stage compression system with intercooler and an internal heat exchanger.
Figure 5.42 Exergy destruction rates of each component in the two-stage compression system with intercooler and an internal heat exchanger.
Figure 5.43 Compressor work associated with the system using carbon dioxide as refrigerant under varying heat rejection pressures.
Figure 5.44 Cooling load associated with the system using carbon dioxide as refrigerant under varying heat rejection pressures.
Figure 5.45 Energetic COP of the system using carbon dioxide as refrigerant under varying gas cooler outlet temperatures.
Figure 5.46 Exergetic COP of the system using carbon dioxide as refrigerant under varying gas cooler outlet temperatures.
Chapter 6: Cost, Environmental Impact and Multi-Objective Optimization of Battery TMSs
Figure 6.1 Sample schematic for the evolutionary algorithm used (adapted from Ghaffarizadeh, 2006).
Figure 6.2 A general pareto optimal curve.
Figure 6.3 Cost rate of exergy destruction for thermal management system components.
Figure 6.4 Cost distribution among investment and exergy destruction rates for the BTMS components.
Figure 6.5 Relationship between compressor exergy destruction rate and investment cost rate.
Figure 6.6 Relationship between condenser exergy destruction rate and investment cost rate.
Figure 6.7 Relationship between evaporator exergy destruction rate and investment cost rate.
Figure 6.8 Relationship between compressor exergy destruction rate and investment cost rate per unit product exergy under different interest rates.
Figure 6.10 Relationship between evaporator exergy destruction rate and investment cost rate per unit product exergy under different interest rates.
Figure 6.11 Total and avoidable cost rates with respect to (a) investment and (b) exergy destruction for the compressor based on various compressor efficiencies.
Figure 6.13 Total and avoidable cost rates with respect to (a) investment and (b) exergy destruction for the evaporator based on various evaporating temperatures.
Figure 6.14 (a) Amount of emissions released and (b) associated imposed cost with respect to varying compressor work under different electricity generation mixes.
Figure 6.15 Illustration of the lithium-ion battery using SimaPro 7.
Figure 6.16 Various environmental impact potentials associated with each battery sub-component.
Figure 6.17 Eco-indicator points associated with production, energy usage and transport of the battery.
Figure 6.18 Percentage contribution of each component to the environmental impact with respect to eco-indicator 99 points.
Figure 6.19 Environmental impact eco-indicator 99 points associated with exergy destruction for thermal management system components.
Figure 6.20 Single objective optimization of BTMS over generations with respect to exergy efficiency.
Figure 6.24 Multi-objective optimization of BTMS with respect to exergy efficiency and total environmental impact rate.
Figure 6.25 Normalized values of different objectives with respect to various optimization functions.
Chapter 7: Case Studies
Figure 7.1 The dependence of the normalized general indicator,
NGInd
, on electricity-generation scenario for four types of cars (adapted from Granovskii
et al.
, 2006).
Figure 7.2 The optimal fraction (β) for hybrid and hypothetical electric cars in the fleet (adapted from Granovskii
et al.
, 2006).
Figure 7.3 Schematic of experimental set up (adapted from Panchal
et al.
, 2016).
Figure 7.4 (a) Air cooling; (b) Water cooling; and (c) CAD of battery cooling set up (Panchal
et al.
, 2016).
Figure 7.5 Voltage profile at C/5,C/2, 1C, 2C, 3C, 4C (adapted from Panchal
et al.
, 2016).
Figure 7.6 Internal resistance profile at 1C, 2C, 3C, 4C (adapted from Panchal
et al.
, 2016).
Figure 7.7 Discharge voltage profile at 1C and 3C and 5 °C, 15 °C, 25 °C, and 35 °C BC (adapted from Panchal
et al.
, 2016).
Figure 7.8 Surface temperature profile at 1C and 3C and 5 °C, 15 °C, 25 °C, and 35 °C BCs (adapted from Panchal
et al.
, 2016).
Figure 7.9 Simulink block diagram for battery model (adapted from Panchal
et al.
, 2016).
Figure 7.10 Comparison of actual and simulated charge voltage profile at 1C at an ambient condition (adapted from Panchal
et al.
, 2016).
Figure 7.11 Comparison of actual and simulated discharge temperature profiles at 1C and 3C at 5 (adapted from Panchal
et al.
, 2016).
Figure 7.12 Comparison of actual and simulated discharge temperature and voltage profile at 1C and 3C at 5 °C, 15 °C, 25 °C, and 35 °C BCs (adapted from Panchal
et al.
, 2016).
Figure 7.13 Picture of modified hybrid test bench for thermal management (Panchal, 2014).
Figure 7.14 Passive air cooling set up (Panchal, 2014).
Figure 7.15 Pouch cell and two cold plates set up (Panchal, 2014).
Figure 7.16 Zig-Zag cold plate set up (active cooling) (Panchal, 2014).
Figure 7.17 U-Turn cold plate set up (active cooling) (Panchal, 2014).
Figure 7.18 Schematic of cooling system flow from bath to upper and lower cold plates (adapted from Panchal, 2014).
Figure 7.19 Exploded view of test rig (Panchal, 2014).
Figure 7.20 CAD drawings of compression rig (Panchal, 2014).
Figure 7.21 LiFePO
4
- 20Ah lithium-ion prismatic pouch cell (Panchal, 2014).
Figure 7.22 Distribution of areas used to determine average surface temperature (Panchal, 2014).
Figure 7.23 Ambient heat flow to compression rig for four coolant temperatures (adapted from Panchal, 2014).
Figure 7.24 Surface temperature profile at 4C discharge and 5°C bath temperature (adapted from Panchal, 2014).
Figure 7.25 Surface temperature profile at 4C discharge and 35 °C bath temperature (adapted from Panchal, 2014).
Figure 7.26 Maximum average surface temperature of battery for discharge rates and coolant/operating temperatures tested (adapted from Panchal, 2014).
Figure 7.27 Difference in average surface temperature between start and end of discharge (adapted from Panchal, 2014).
Figure 7.28 Average heat flux at 1C, 2C, 3C, 4C discharge rates and different boundary conditions (adapted from Panchal, 2014).
Figure 7.29 Peak heat flux at 1C, 2C, 3C, 4C discharge rates and different boundary conditions (adapted from Panchal, 2014).
Figure 7.30 Heat generation rate at 2C discharge and different bath temperatures (adapted from Panchal, 2014).
Figure 7.31 Battery voltage versus depth of discharge (adapted from Panchal, 2014).
Figure 7.32 Total heat generated at different discharge rates and different boundary conditions (adapted from Panchal, 2014).
Figure 7.33 Effect of operating temperatures on discharge capacities (adapted from Panchal, 2014).
Figure 7.34 Schematic of the proposed thermal management systems (un-scaled) (adapted from Ramandi
et al.
, 2011).
Figure 7.35 Independence tests for single PCM shell at ambient temperature of 318 K (adapted from Ramandi
et al.
, 2011).
Figure 7.36 Comparison of predictions with past data of Al-Hallaj
et al.
, 2006 (Ramandi
et al.
, 2011).
Figure 7.37 Liquid fraction of PCMs in shells for single PCM shell system (insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.38 Battery temperature change during operation for single PCM shell (insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.39 Liquid fraction of PCM-1 after 2.5 hours for a single PCM shell (insulated walls) (Ramandi
et al.
, 2011).
Figure 7.40 Liquid fraction of PCM in first and second shell for double systems (insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.41 Battery temperature change for double PCM shell (insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.42 Liquid fraction of PCMs in shells for single PCM shell (non-insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.43 Battery temperature change for single PCM shell (non-insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.44 Liquid Fraction of PCM-1 after 30 minutes for single PCM shell (non-insulated) (Ramandi
et al.
, 2011).
Figure 7.45 Exergy analysis result for different PCMs in single PCM shell (insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.46 Exergy analysis result for different PCMs in double PCM shell (insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.47 Effects of ambient temperature (single PCM shell; insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.48 Effect of ambient temperature (double PCM shell; insulated walls) (adapted from Ramandi
et al.
, 2011).
Figure 7.49 A schematic diagram of the proposed PCM testing system (Zafar, 2015).
Figure 7.50 Instruments for experimental measurements (Zafar, 2015).
Figure 7.51 Illustration of the system for discharge (a) side view, (b) top view (Zafar, 2015).
Figure 7.52 dry fit set up of the battery and the PCM jacket (Zafar, 2015).
Figure 7.53 Illustration of the battery cooling test set up (Zafar, 2015).
Figure 7.54 Experimental layout of the first set of experiments (modified from Zafar, 2015).
Figure 7.55 Experimental layout of the second set of experiments (modified from Zafar, 2015).
Figure 7.56 Experimental layout of the third set of experiments (modified from Zafar, 2015).
Figure 7.57 Schematic diagram of the charging, storage and discharging process for the PCM (adapted from Dincer and Rosen, 2013).
Figure 7.58 Graphical illustration of water and refrigerant masses for each fraction (Zafar, 2015).
Figure 7.59 R134a clathrates in tubes (a) 0.15, (b) 0.2, (c) 0.25, (d) 0.3, (e) 0.35 and (f) 0.4 refrigerant mass fraction at 276 K (Zafar, 2015).
Figure 7.60 R134a clathrate times for onset and end set at different refrigerant mass fractions at 278 K (modified from Zafar, 2015).
Figure 7.61 Total battery cooling down time using each PCM (adapted from Zafar, 2015).
Figure 7.62 Battery temperature at cutoff voltage (adapted from Zafar, 2015).
Figure 7.63 Battery run times until the cutoff voltage (adapted from Zafar, 2015).
Figure 7.64 End set energy and exergy values at different refrigerant mass fractions for 278 K bath temperature (adapted from Zafar, 2015).
Figure 7.65 End set energy and exergy values at different refrigerant mass fractions for 276 K bath temperature (adapted from Zafar, 2015).
Figure 7.66 Base PCM end set energy and exergy values for charging process at 276 K and 278 K (adapted from Zafar, 2015).
Figure 7.67 Thermoeconomic variable values of each PCM (adapted from Zafar, 2015).
Figure 7.68 Energy costs of producing and using PCM (adapted from Zafar, 2015).
Figure 7.69 Costs of producing 100 units of each PCMs (adapted from Zafar, 2015).
Chapter 8: Alternative Dimensions and Future Expectations
Figure 8.1 Risk barriers perceived by consumers regarding electric vehicle technology (adapted from Bessenbach and Wallrapp, 2013).
Figure 8.2 Direct and indirect networks effects (adapted from Meyer, 2012).
Figure 8.3 Past evolution and future expectation of the H&EV technologies (adapted from Dijk, 2014).
Figure 8.4 The concept of dynamic wireless charging system on special highway lanes (adapted from Miller
et al.
, 2014).
Figure 8.5 Futuristic concept of smart grid and V2X systems.
Figure 8.6 Illustration of a battery swapping station (adapted from Davies, 2013).
Figure 8.7 Fundamental steps of EV battery between primary use and recycling (adapted from Neubauer and Pesaran, 2010).
Figure 8.8 Schematics of the repurposing processes for a used EV Li-ion battery pack (adapted from Lih
et al.
, 2012).
Figure 8.9 Illustrative example of a magnetic thermal management system diagram integrated into EV battery pack (adapted from Cooltech, 2015).
Figure 8.10 Representation of piezoelectic fan having horizontal vibration over a heat sink.
List of Tables
Chapter 1: Introductory Aspects of Electric Vehicles
Table 1.1 Characteristics of vehicles with different hybridization rates (adapted from Center for Advanced Automotive Technology, 2015)
Table 1.2 Charging power levels
Table 1.3 Charging infrastructure costs
Table 1.4 Vehicle charging standards
Table 1.5 Charging schemes for electric vehicles
Table 1.6 Special consumption tax classification categories for new vehicle sales
a)
Table 1.7 Passenger car market according to the engine/electric motor size for 2009–2013
Table 1.8 Passenger car market according to average emission values for 2001–2013
Table 1.9 SWOT analysis for domestic and global market penetration of H&EVs
Chapter 2: Electric Vehicle Battery Technologies
Table 2.1 Battery characteristics for today's most common battery chemistries
Table 2.2 Energy densities of some common Li-ion chemistries with respect to composition of their cathode
Table 2.3 Comparison of Li-ion battery cathode and anode materials
Table 2.4 The main SOC determination and cell equalization methods used in EV BMSs
Table 2.5 Basic tests typically conducted on the EV batteries
Chapter 3: Phase Change Materials for Passive TMSs
Table 3.1 Typical parameters of thermal energy storage (TES) systems
Table 3.2 Essential properties desired in the selection of the suiTable PCM
Table 3.3 List of some commonly used PCMs
Table 3.4 Types of encapsulation for PCMs
Table 3.5 Variations of heat exchanger length and shell diameter with respect to tube diameter
Table 3.6 Design parameters and their range of variation in the case of helical tubes
Table 3.7 Soft copper tube specifications for optimization
Table 3.8 Cell distribution for the three cases considered in the grid independence tests for the sphere
Chapter 4: Simulation and Experimental Investigation of Battery TMSs
Table 4.1 Effect of temperature variations on the specific heats
Table 4.2 Thermo-physical properties of materials for simulation
Table 4.3 Commonly used foams for BTMS applications
Table 4.4 Sample instrumentation list for general TMS experimentations
Table 4.5 List of commonly used medium-speed CAN bus signals received from the vehicle
Table 4.6 Critical temperatures in the cell for different models
Table 4.7 Comparison between temperatures with and without PCM in between the cells
Table 4.8 Temperatures after 50 minutes for different zones
Table 4.9 (a) Dimensions of submodule (without applying the PCM jackets) and (b) the properties of components
Table 4.10 Maximum temperature in different zones in the submodule with and without the PCM
Table 4.11 Rakes locations in submodule to monitor the temperature distribution
Table 4.12 Samples of PCM and nano-particles prepared for the tests
Table 4.13 Refrigerant temperatures used to validate the model
Table 4.14 Comparison of results between the experimentation and the model
Chapter 5: Energy and Exergy Analyses of Battery TMSs
Table 5.1 Energetic and exergetic COP equations used in the analysis
Table 5.2 Range of parameters commonly used in BTMSs
Table 5.3 Characteristics of R134a and various alternative refrigerants
a
Table 5.4 Exergy destruction rates for each component in the TMS
Table 5.5 Operational parameters of a standard EV TMS for various refrigerants at baseline conditions
Table 5.6 Operating parameters of studied EV BTMS with various refrigerants at baseline conditions
Table 5.7 Exergetic COP and exergy destruction rate associated with the refrigerant cycle of different transcritical carbon dioxide–based EV BTMSs
Chapter 6: Cost, Environmental Impact and Multi-Objective Optimization of Battery TMSs
Table 6.1 Fuel and product definitions with respect to the system
Table 6.2 Environmental impact correlations (eco-indicator 99) developed based on the compiled data
Table 6.3 Normalization used for eco-indicator 99 H/H
Table 6.4 Major battery components used in the LCA analysis and their corresponding weights
Table 6.5 Common constraints associated with the decision variables selected for the BTMS
Table 6.6 Exergy flow rates, cost flow rates and the unit exergy cost associated with each state of BTMS
Table 6.7 Investment cost rate, cost rate of exergy destruction, total cost rate, exergoeconomic factor and relative cost difference associated with the BTMS components
Table 6.8 Comparison of total and avoidable cost rates of the respective exergoeconomic factors associated with the components of the BTMS
Table 6.9 Exergy flow rates, environmental impact due flow rates and the unit environmental impact cost associated with each state of BTMS
Table 6.10 Total environmental impact, exergoenvironmental factor and relative difference of exergy-related environmental impacts associated with the BTMS components
Table 6.11 Environmental impact related to the exergy destruction rate for BTMS components using electricity generation mixes for various countries
Table 6.12 Decision variables for the base case design under various optimization criteria
Table 6.15 Environmental analysis results for the base case design under various optimization criteria
Chapter 7: Case Studies
Table 7.1 Economic characteristics for four vehicle technologies
Table 7.2 Gaseous emissions per kilogram of curb mass of a typical vehicle
Table 7.3 Environmental impact associated with vehicle production stages
Table 7.4 The environmental impact related to the production of nickel metal hydride (NiMH) batteries and polymer exchange membrane fuel cell (PEMFC) stacks
Table 7.5 Material inventory of a polymer exchange membrane fuel cell stack
Table 7.6 Greenhouse gas and air pollution emissions per MJ of electricity produced
Table 7.7 Greenhouse gas and air pollution emissions per MJ (LHV) of hydrogen and gasoline from combustion in fuel cell and internal combustion engine vehicles
Table 7.8 Greenhouse gas/air pollution emissions with respect to fuel utilization stage and overall environmental impact for various propulsion systems
Table 7.9 Normalized economic and environmental indicators for four types of cars
Table 7.10 Optimal relationship in fleet between different types of cars
Table 7.11 Normalized economic and environmental indicators for hybrid and hypothetical electric car with different efficiencies for on-board electricity generation
Table 7.12 Positions of thermocouple locations
Table 7.13 LiFePO
4
- 20Ah Lithium-ion prismatic pouch cell specifications
Table 7.14 Experimental plan
Table 7.15 X and Y component lengths of thermocouple areas
Table 7.16 Ambient heat flow to compression rig for different coolant temperature
Table 7.17 maximum average battery surface temperature for different discharge rates and bath temperatures
Table 7.18 Linear fit for four different bath temperatures
Table 7.19 Summary of average heat flux at 1C, 2C, 3C, 4C discharge rates and different boundary conditions
Table 7.20 Summary of peak heat flux at 1C, 2C, 3C, 4C discharge rates and different boundary conditions
Table 7.21 Summary of maximum heat generation rate at 1C, 2C, 3C, 4C discharge rates and different boundary conditions
Table 7.22 Summary of total heat generated at 1C, 2C, 3C, 4C discharge rates and different boundary conditions
Table 7.23 Summary of discharge capacities at 1C, 2C, 3C, 4C discharge rates and different boundary conditions
Table 7.24 Summary of discharge times at 1C, 2C, 3C, 4C discharge rates and different boundary conditions
Table 7.25 Battery specifications
Table 7.26 Specification of PCMs utilized in thermal management systems
Table 7.27 Values of water and refrigerant mass for each fraction
Table 7.28 Energy and exergy values for onset and end set times of charging process of base clathrate at 278 K bath temperature
Table 7.29 Energy and exergy values for onset and end set times of charging process of base clathrate at 276 K bath temperature
Automotive Series
Series Editor: Thomas Kurfess
Automotive Aerodynamics
Katz
April 2016
The Global Automotive Industry
Nieuwenhuis
September 2015
and Wells
Vehicle Dynamics
Meywerk
May 2015
Vehicle Gearbox Noise and
T{\uring}ma
April 2014
Vibration: Measurement, Signal
Analysis, Signal Processing and
Noise Reduction Measures
Modeling and Control of
Eriksson and
April 2014
Engines and Drivelines
Nielsen
Modelling, Simulation and
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March 2014
Control of Two-Wheeled Vehicles
and Savaresi
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December 2013
Automotive Applications: Structural
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Guide to Load Analysis for Durability
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in Vehicle Engineering
and Speckert
Thermal Management of Electric Vehicle Battery Systems
Ibrahim Dinçer
University of Ontario Institute of Technology, Canada
Halil S. Hamut
The Scientific and Technological Research Council of Turkey-Marmara Research Center, Turkey
Nader Javani
Yildiz Technical University, Turkey
This edition first published 2017
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Library of Congress Cataloging-in-Publication Data
Names: Dinçer, İbrahim, 1964- author. | Hamut, Halil S., author. | Javani, Nader.
Title: Thermal management of electric vehicle battery systems / İbrahim Dinçer, Halil S. Hamut, Nader Javani.
Description: Chichester, West Sussex, United Kingdom : John Wiley & Sons, Inc., [2017] | Includes bibliographical references and index.
Identifiers: LCCN 2016041896| ISBN 9781118900246 (cloth) | ISBN 9781118900222 (epub) | ISBN 9781118900215 (Adobe PDF)
Subjects: LCSH: Electric vehicles-Batteries-Cooling.
Classification: LCC TL220 .D56 2017 | DDC 629.25/024-dc23 LC record available at https://lccn.loc.gov/2016041896
A catalogue record for this book is available from the British Library.
Cover Design: Wiley
Cover Images: Courtesy of the authors
Preface
Over the last few decades, concerns over the dependence and price instability of limited fossil fuels as well as environmental pollution and global warming have encouraged researchers, scientists and engineers to conduct more proactive research on vehicles with alternative energy sources. Today, electric vehicles (EVs) are starting to replace their conventional counterparts, due to the recent improvements in battery technologies, as they offer diversification of energy resources, load equalization of power, improved sustainability as well as lower emissions and operating costs.
Through this transition towards EVs, the vehicle related problems are mainly composed of the battery and its performance. In order to achieve the most ideal performance, the discrepancy between the optimum and operating conditions of the batteries need to be reduced significantly, which requires the effective use of thermal management systems (TMSs). Since EVs have a wide range of battery characteristics, size and weight limitations, and variable loads, achieving the most optimal battery thermal management system design, configuration and operation play a crucial role in the success and wide adoption of this technology.
In this book, electric vehicles, their architectures, along with the utilized battery chemistries, are initially introduced to the readers to provide the necessary background information followed by a thorough examination of various conventional and state-of-the-art EV battery TMSs (including phase change materials) that are currently used or potentially proposed to be used in the industry. Through the latter chapters, the readers are provided with the tools, methodology and procedures to select/develop the right thermal management designs, configurations and parameters for their battery applications under various operating conditions, and are guided to set up, instrument and operate their TMSs in the most efficient, cost effective and environmentally benign manners using exergy, exergoeconomic and exergoenvironmental analyses. Moreover, a further step is taken over the current technical issues and limitations, and a wider perspective is adopted by examining more subtle factors that will ultimately determine the success and wide adoption of these technologies and elaborate what we can expect to see in the near future in terms of EV technologies and trends as well as the compatible TMSs. Finally, various case studies in real-life applications are presented that employ the tools, methodology and procedures presented throughout the book to further illustrate their efficacy on the design, development and optimization of electric vehicle battery thermal management systems.
The book includes step-by-step instructions along with practical codes, models and economic and environmental databases for readers for the design, analysis, multi-criteria assessment and improvement of thermodynamic systems which are often not included in other solely academic textbooks. It also incorporates a large number of numerical examples and case studies, both at the end of each chapter and at the end of the book, which provide the reader with a substantial learning experience in assessment and design of practical applications. The book is designed to be an invaluable handbook for practicing engineers, researchers and graduate students in mainstream engineering fields of mechanical and chemical engineering. It consists of eight chapters with topics that range from broad definitions of alternative vehicle technologies to the detailed thermodynamic modelling of specific applications, by considering energy and exergy efficiency, economic and environmental considerations and sustainability aspects.
Chapter 1 introduces the current alternative vehicles in terms of their configurations and architectures, hybridization rates, energy storage systems as well as the emerging grid connections. It also examines the individual thermal management systems of the vehicle and elaborates on the sustainability issues.
Chapter 2 provides in-depth information in the existing and near future battery chemistries and conducts evaluations with respect to their performance, cost and technological readiness. Moreover, different battery management methodologies and techniques are provided with the focus on battery state estimation and charge equalization to increase the performance and longevity of the cells. The steps that are necessary to develop, manufacture and validate the batteries from cell to pack levels are also provided at the end of the chapter.
Chapter 3 introduces and classifies the basic properties/types of phase change materials, their advantages/drawbacks as well as methods to measure and improve their heat transfer capabilities. Moreover, novel methods to replace liquid battery TMSs with lighter, cheaper and more effective PCM alternatives are also presented for various applications.
In Chapter 4, a walkthrough of the necessary steps is provided to develop representative models of the battery from a cell to a pack level, achieve reliable simulations, form correct set ups of the data acquisition hardware and software, as well as to use the right procedures for the instrumentation of the battery and the vehicle in the experimental set up. The main focus is given to the battery cell and submodule simulations to provide the fundamental concepts behind the heat dissipation in the cell and heat propagation throughout the battery pack. The chapter is designed to provide an in-depth understanding of the cell electrochemistry as well as the thermodynamic properties of the thermal management systems before more detailed analysis are conducted in the next chapters.
In Chapter 5, various types of state-of-the-art thermal management systems are examined and assessed for electric vehicle battery systems. Subsequently, step-by-step thermodynamic modelling of a real TMS is conducted and the major system components are evaluated under various parameters and real life constraints with respect to energy and exergy criteria to provide the readers with the methods as well as the corresponding results of the analyses. The procedures are explained in each step and generic and widely used parameters are utilized as much as possible to enable the readers to incorporate these analyses to the systems they might be working on.
A walkthrough of developing exergoeconomic and exergoenvironmental analyses are presented in Chapter 6, in order to give the readers the necessary tools to analyze the investment costs associated with their system components and assess the economic feasibility of the suggested improvements as well as the environmental impact (using LCA). Procedures to determine the associated exergy streams are shown and a databank of investment/operating cost and environmental impact correlations are provided for the readers to provide assistance in modelling their system components with an extensive accuracy without the need of cumbersome experimental relationships. Finally, the vital steps for conducting a multi-objective optimization study for BTMS is carried on, where the results from exergy, exergoeconomic and exergoenvironmental analyses are used according to the developed objective functions and system constraints in order to illustrate the methods to optimize the system parameters under different operating conditions with respect to various criteria using Pareto Optimal optimization techniques.
Furthermore, various case studies are provided in Chapter 7 that employ the tools, methodology and procedures presented throughout the book and conduct analyses on real-life applications to further illustrate their efficacy on the design, development and optimization of electric vehicle battery thermal management systems.
Finally, Chapter 8 presents a wider perspective on electric vehicle technologies and thermal management systems by examining the remaining outstanding challenges and emerging technologies that might provide the necessary solutions for the success and wide adoption of these technologies. Furthermore, various TMS technologies that are currently under development for an extensive range of applications are introduced to provide an indication of what the BTMS might incorporate in the future.
We hope that this book brings a new dimension to EV battery thermal management systems and enables the readers to develop novel designs and products that offer better solutions to existing challenges and contribute to achieving a more sustainable future.
İbrahim DinçerHalil S. HamutNader Javani May 2016
Acknowledgements
The illustrations and supporting materials provided by several past/current graduate students and postdoctoral research fellows of Professor Dincer for various case studies in the book are gratefully acknowledged, including Satyam Panchal, Sayem Zafar, Masoud Yousef Ramandi, David MacPhee and Mikhail Granovskii.
We also acknowledge the support provided by the Natural Sciences and Engineering Research Council of Canada, General Motors Canada in Oshawa, and Marmara Research Center of The Scientific and Technological Research Council of Turkey (TUBITAK Marmara Research Center).
Last but not least, we warmly thank our families for their support, motivation, patience and understanding.
İbrahim DinçerHalil S. HamutNader Javani May 2016
Chapter 1Introductory Aspects of Electric Vehicles
1.1 Introduction
Energy is used in all aspects of life, and it is considered an essential part of the existence of the ecosystem and human civilization. Thus, energy-related issues are one of the most important problems that we face in the twenty-first century. With the onset of industrialization and globalization, the demand for energy has increased exponentially over the past decades. Especially with a population growth of faster than 2% in most countries, along with improvements on lifestyles that are linked to energy demand, the need for energy is ever-increasing. Based on the current global energy consumption pattern, it is predicted that the world energy consumption will increase by over 50% before 2030. Thus, based on this pervasive use of global energy resources, energy sustainability is becoming a global necessity and affects most of the civilization (Dincer, 2010).
Currently, the world relies heavily on fossil fuels such as oil, natural gas and coal, which provide almost 80% of the global energy demands, to meet its energy requirements. It is estimated that most of large-scale energy production and consumption of energy causes degradation of the environment as they are
