Chair’s Opening Remarks

Battery System Engineering Under Extreme Constraints: Yield, Fast-Charge Durability & Pack-Level Trade-Offs at Scale

Brian Engle, Chairman, NAATBatt international; Chair, SAE Battery Standards Steering Committee

Aluminium Battery Enclosures: Managing Load Paths, Thermal Integration & Manufacturing at Scale

As battery architectures move to cell-to-pack and cell-to-chassis, the enclosure is no longer a housing — it is a primary structural member, thermal interface, and safety system. This creates competing requirements across crash performance, stiffness, thermal behaviour, manufacturability, and cost that cannot be solved independently.

This session focuses on how OEMs and suppliers are engineering aluminium enclosure systems that can carry vehicle loads, control deformation during crash events, manage thermal loads under fast charging, and remain manufacturable at scale.

The discussion will examine:

• Load path design and crash performance, including intrusion limits, energy absorption, and aluminium vs. steel trade-offs in side impact and underbody events

• Material and joining strategies, including alloy selection, extrusion vs. sheet architectures, weld vs. adhesive bonding, and the impact on stiffness, fatigue, and corrosion

• Thermal integration at enclosure level, including coolant routing, interface resistance, and containment of thermal runaway within large-format packs

• Manufacturing constraints, including extrusion tolerances, flatness control, joining distortion, and compatibility with gigacasting and high-volume assembly

• Cost and sustainability trade-offs, including scrap rates, recyclability of multi-material systems, and embedded carbon across different enclosure architectures

The goal is to understand how enclosure design decisions impact pack-level performance, safety margins, and $/kWh at scale, and where current designs are still failing to meet OEM requirements.

Fastening in the Age of Structural Battery Packs: Lightweight Joining for High-Energy EV Architectures

Ryan Ward, Head of Engineering, Arnold Fastening Systems

As EV platforms evolve toward cell-to-pack and cell-to-chassis architectures, the battery pack is no longer a passive enclosure — it is a primary structural component of the vehicle. At the same time, OEMs are aggressively reducing mass, integrating gigacast structures, and increasing energy density.

This creates a critical engineering challenge: how to achieve lightweight, crash-resilient, thermally stable battery pack integration without increasing assembly complexity or compromising safety. Traditional fastening strategies are no longer sufficient for multi-material, adhesive-integrated, high-voltage pack systems.

This session explores next-generation fastening and hybrid joining solutions designed for structural battery architectures, focusing on lightweighting, automation readiness, and structural integrity in high-energy EV platforms.

• Evaluate fastening strategies for structural battery packs, including load transfer, fatigue resistance, and crash performance.

• Assess hybrid adhesive–mechanical joining systems to balance lightweighting, durability, and assembly robustness.

• Understand multi-material joining challenges in aluminium-intensive and gigacast EV platforms.

• Identify fastening solutions that support high-voltage safety and corrosion resistance in battery environments.
  

• Optimise assembly efficiency and automation compatibility to reduce cycle time and overall $/kWh.

Gigacasting & Battery Integration: Rethinking EV Battery Architecture for Cast Vehicle Platforms

As OEMs scale gigacasting, vehicle architectures are shifting toward large aluminium structures that reduce part count and assembly complexity — but fundamentally change how battery packs integrate into the vehicle.

Gigacast platforms alter load paths, stiffness, and packaging constraints, making traditional pack enclosures and mounting strategies increasingly obsolete. In response, engineers are moving toward integrated solutions such as cast-to-pack architectures, adhesive load sharing, and reduced fastener strategies, where the battery becomes a structural element.

This session examines how OEMs are adapting battery design to these new conditions — including structural stress management, thermal integration within constrained geometries, and maintaining crash performance while reducing system complexity.

The focus is on the engineering trade-offs of integrating battery systems into cast vehicle platforms, and the implications for durability, safety, and serviceability.

A clear, pragmatic view of battery integration in the era of gigacast architectures.

• Understand how gigacasting changes vehicle load paths, structural behaviour, and battery pack integration requirements.

• Evaluate cast-to-pack and structural battery approaches, including adhesive bonding, fastener reduction, and load sharing strategies.

• Assess the impact of gigacast architectures on thermal system design, packaging constraints, and serviceability.

• Identify key challenges in maintaining crash safety and durability when integrating batteries into structural cast components.

• Develop a practical framework for designing battery systems within next-generation cast vehicle platforms.

Structural Battery Packs: Designing Load-Bearing Energy Systems Without Compromising Safety

Designing structural packs requires reconciling conflicting requirements. Increased stiffness improves vehicle dynamics but can reduce energy absorption in crash events. Integrating cooling systems within structural elements introduces complexity in sealing, durability, and thermal uniformity. At the same time, fire containment and propagation resistance must be maintained within architectures that minimise redundancy and enclosure mass.

This session provides a practical, engineering-led examination of how OEMs and suppliers are developing structural battery systems that work in real vehicle platforms. It explores how load paths are managed through the pack, how materials and joining strategies are selected to balance stiffness and crash performance, and how thermal systems are integrated without compromising structural integrity.

Rather than focusing on conceptual designs, the discussion centres on the trade-offs required to deliver structural efficiency while maintaining safety, durability, and manufacturability at scale.

As vehicle and battery architectures converge, understanding how to design structural packs that meet real-world performance and safety requirements has become a critical priority for EV engineers.

This session offers a clear, pragmatic view of load-bearing battery system design in next-generation vehicle platforms.

• Understand how structural battery packs redistribute vehicle load paths and impact overall structural behaviour.

• Evaluate the trade-offs between stiffness, crash energy absorption, and durability in load-bearing battery architectures.

• Assess strategies for integrating thermal management systems within structural packs while maintaining performance and reliability.

• Identify approaches to fire containment and thermal propagation resistance in reduced-mass, highly integrated designs.

• Develop a practical framework for designing structural battery systems that are safe, manufacturable, and scalable.

Driving Faster Development with Modeling & Simulation for Cost-Efficient Thermal Integration

Kush Patel, Application Engineer, Henkel

As EV platforms become more compact, energy-dense, and thermally constrained, battery pack integration leaves little room for error. Thermal management can no longer be treated as a late-stage validation step; it must be engineered correctly from the concept phase. With physical prototyping too slow and costly for today’s development timelines, this session explores how early-stage modeling and simulation are accelerating battery system development and de-risking integration decisions before hardware is built. Covering predictive thermal modeling, materials-level digital validation, design trade-off optimisation, and process simulation, the discussion demonstrates how engineers can reduce prototype iterations, improve first-pass success, and deliver cost-efficient, manufacturable thermal solutions at scale.

• Understand how early-stage modeling reduces battery thermal integration risk

• Evaluate how material-level data can improve pack-level simulation accuracy

• Assess design and process trade-offs before physical prototyping

• Explore strategies to shorten development cycles while maintaining safety and performance

• Identify scalable, manufacturable thermal solutions for next-generation EV platforms

Thermal Runaway Propagation Is a Pack Architecture Problem — Not a Cell Problem

As EV platforms transition toward cell-to-pack (CTP) and cell-to-chassis architectures, battery systems are becoming more energy-dense, structurally integrated, and space-constrained. Interstitial gaps are shrinking. Firewalls and traditional passive barriers are being reduced. Structural members are now directly adjacent to active cells.

In this environment, thermal runaway propagation is no longer solely a cell chemistry challenge — it is fundamentally a pack architecture problem.

This session reframes the discussion from material-level heat spreading to system-level propagation control, examining how passive thermal materials — specifically engineered graphite solutions — can be integrated directly into structural battery design to manage, redirect, and contain thermal events.

• Assess how CTP and cell-to-chassis architectures alter thermal runaway risk, including spacing reduction, structural load-path interaction, and energy density vs safety trade-offs.

• Optimise anisotropic thermal strategies, controlling in-plane and through-plane heat flow to limit cell-to-cell propagation and protect structural elements.

• Design passive heat routing and venting pathways to manage pressure, hot gas flow, and secondary ignition risk.

• Evaluate graphite as a passive propagation control layer, integrated within structural pack designs.
  

• Compare graphite with aerogel and ceramic barriers, balancing weight, manufacturability, cost, and scalability for high-volume EV production.

Morning Networking Break

Thermal Runaway Containment in Structural Battery Packs: Engineering Safety in Load-Bearing Energy Systems

As EV manufacturers adopt structural battery pack architectures to reduce vehicle mass and simplify manufacturing, engineers face a new safety challenge: ensuring effective containment of thermal runaway events within battery systems that also serve as load-bearing structural elements. Unlike traditional modular packs, structural designs often reduce internal separation and increase mechanical integration with the vehicle chassis, raising the risk of thermal propagation, gas accumulation, and structural damage during failure events.

This session explores how OEMs are developing advanced strategies to detect, isolate, and contain thermal runaway within structural packs, including thermal barrier materials, venting and off-gas management systems, and structural reinforcement approaches that prevent failure propagation. Experts will examine how pack-level safety engineering, thermal modelling, and crash integration strategies are being used to ensure that next-generation structural battery architectures meet the highest safety and regulatory standards while maintaining the mass and manufacturing advantages they promise.

• Understand how structural battery architectures change thermal runaway behaviour, including propagation pathways and gas management challenges.

• Evaluate containment strategies, including thermal barriers, venting systems, and structural reinforcement approaches.

• Assess how reduced modularity and increased integration impact failure isolation and safety performance.

• Identify the role of thermal modelling and pack-level simulation in predicting and mitigating failure events.

• Develop a practical framework for designing structural battery systems that meet safety and regulatory requirements under failure conditions.

From Mobility to Energy Storage: How Adhesive Technologies Bridge BEV and BESS Battery Design

Niranjan Malvadkar, Ph.D. Research Scientist, DuPont

Battery Electric Vehicle (BEV) battery packs and Battery Energy Storage System (BESS) battery modules share similar architectures, operating requirements, and performance constraints, driven by common underlying battery technologies. In both applications, system design is governed by the need for long battery cycle life, cost-efficient manufacturing and safety performance.

Adhesive technologies have become critical enablers in meeting these requirements and are now integral to modern BEV and BESS battery assembly strategies. DuPont’s multifunctional materials provide structural bonding while simultaneously delivering electrical insulation and controlled thermal conductivity—functions that are essential to mechanical integrity, thermal management, and overall system safety. 

This presentation will: 

• Examine adhesive technologies used in both BEV battery packs and BESS battery modules

• Focus on the importance of adhesive technologies for the assembly, durability, safety, and cost-efficient production of both Battery Electric Vehicle (BEV) battery packs and Battery Energy Storage Systems (BESS) battery modules.

Halogen-Free Flame Retardancy in the Age of 800V Battery Architectures

Replacing Metal Without Increasing Risk: Advanced Flame-Retardant & Structural Polymers for Next-Generation EV Battery Packs

Khaled Rashwan, Key Account Manager, Kingfa Sci. & Tech. Co., Ltd.

As EV platforms transition toward 800V architectures, larger-format cells, and cell-to-pack integration, OEMs face a critical balancing act: reducing weight and cost while improving fire safety, dielectric performance, and structural robustness. Traditional metal-heavy pack designs add mass and assembly complexity, yet replacing metal with polymers introduces new concerns around flame retardancy, arc tracking, dimensional stability, and crash durability.

This session examines how next-generation halogen-free flame-retardant polymers and reinforced engineering thermoplastics are enabling lightweight battery module and pack structures without compromising safety or compliance. By addressing high-voltage insulation, propagation resistance, structural load management, and recyclability, the discussion focuses on how material systems can solve emerging OEM challenges in scalable EV battery manufacturing.

• Evaluate material strategies for 800V+ battery systems, including high CTI performance, arc tracking resistance, and dielectric stability under elevated temperatures.

• Assess halogen-free flame-retardant solutions for battery modules and enclosures that meet fire safety standards without adding excessive weight or complexity.

• Compare reinforced thermoplastics and hybrid metal-polymer solutions for structural battery components, considering crash performance, fatigue resistance, and thermal cycling durability.

• Understand the trade-offs between metal and advanced polymers in cell-to-pack and structural pack architectures, balancing stiffness, weight, manufacturability, and cost.
  

• Identify scalable, recyclable material systems that align with global sustainability mandates and high-volume EV production requirements.

Silicon Anodes at Scale: Managing Expansion, Durability & Safety in Next-Generation EV Batteries

Silicon-dominant anodes promise significant gains in energy density and fast-charge capability — yet volume expansion, particle fracture, and binder failure remain major barriers to scalable deployment in EV platforms. OEMs face a critical challenge: how to unlock silicon’s capacity advantage without sacrificing cycle life, manufacturability, or safety margins.

This session explores the materials science behind silicon anode integration at scale, focusing on binder chemistry, mechanical resilience, and electrode architecture optimisation. It examines how advanced polymer and silicone-based binder systems can accommodate expansion stresses, maintain electrode integrity, and enable high-performance silicon blends to transition from pilot lines to gigafactory production.

• Evaluate the mechanical and electrochemical challenges associated with silicon-rich anodes in high-energy EV cells.

• Assess binder material strategies that enable expansion tolerance while maintaining adhesion and conductivity.

• Analyse trade-offs between energy density gains and durability risks in silicon-blended electrode designs.

• Understand process and manufacturing considerations for integrating advanced binders into gigafactory-scale production.
  

• Identify scalable material solutions that enable higher energy density without increasing warranty exposure or safety risk.

Reducing Scrap and Improving Yield in Gigafactory Battery Manufacturing: Materials Engineering for Scalable EV Production

TBC – EVONIK Industries

As systems scale toward higher energy density, faster charging, and gigafactory-level production volumes, performance is no longer defined by chemistry alone — manufacturing yield, process stability, thermal resilience, and long-term durability are now equally decisive.

This session examines how advanced specialty materials and process-enabling technologies are addressing these pressures across the battery value chain, from electrode additives that improve slurry wetting, dispersion, and coating uniformity, to fumed metal oxides enhancing cathode and separator performance, and high-performance polymers providing electrical insulation and thermal stability at module level.

It will explore how optimised coating and dispersing processes reduce defects and scrap in high-volume production, how fire-resistant coatings and ceramic-enhanced separators strengthen pack-level safety and thermal runaway resistance, and how next-generation innovations — including graphene-enhanced materials and additives for emerging solid-state and high-voltage chemistries — are preparing manufacturers for the next wave of EV battery performance and industrialisation.

Understand how advanced additives and specialty materials improve electrode quality, yield, and cycle life

• Evaluate the role of functional materials in reducing scrap and enabling gigafactory-scale production

• Assess fire protection and separator strategies to enhance pack-level safety

• Explore how graphene and next-generation additives may improve energy density and charging performance

• Identify scalable material solutions aligned with future solid-state and high-performance battery architectures

Networking Lunch Break

How Testing Itself is Evolving In Response to Next-Generation Battery Architectures

The Industry is shifting from “Does it pass the standard?” To “Do we truly understand how it fails at scale?”

As OEMs transition toward larger prismatic and pouch cells, cell-to-pack (CTP) integration, and structural battery architectures, traditional compliance testing such as UN 38.3 is no longer sufficient to characterise real-world failure behaviour. Battery packs are now structural members of the vehicle, energy density is rising, and fast-charging loads are intensifying — yet validation methodologies have historically remained compliance-driven rather than engineering-led.

This session explores how advanced pack-level abuse testing, controlled thermal runaway characterisation, high C-rate durability validation, and enhanced instrumentation are shifting the industry from simple pass/fail certification to data-rich failure analysis. By combining propagation studies, real-world duty cycle simulation, and evolving regulatory alignment, the discussion addresses how OEMs can better quantify risk, design mitigation strategies, and reduce warranty exposure in next-generation EV platforms.

• Evaluate whether traditional standards (e.g., UN 38.3, IEC 62660, UL, SAE) adequately reflect failure risks in large-format, CTP, and structural battery packs.

• Quantify thermal runaway and propagation risk using controlled initiation testing, gas and pressure analysis, and multi-cell propagation studies to inform pack architecture decisions.

• Assess abuse testing methodologies (nail penetration, crush, overcharge, thermal shock) for next-generation high-energy cells and structural pack designs.

• Interpret engineering-grade failure data to improve barrier validation, fire mitigation strategy development, and compliance with evolving US fire and transport regulations.
  

• Model real-world durability and fast-charge degradation through high C-rate cycling, environmental chamber integration, and accelerated lifetime testing to reduce long-term warranty exposure.

Domestic Battery Manufacturing in a Volatile Market: What Actually Scales?

The race to localise battery production in the United States has accelerated under the Inflation Reduction Act (IRA), yet the reality of scaling domestic cell manufacturing remains complex, capital-intensive, and highly volatile. Gigafactory announcements are easy; achieving stable yields, competitive $/kWh, and sustainable margins is not.

This session delivers a candid, engineering-led perspective on what actually scales in U.S. battery manufacturing — examining factory economics, capital intensity, production strategy decisions, and the operational trade-offs between domestic build-out and global partnerships. Rather than focusing on theoretical capacity targets, the discussion centres on industrial execution, risk mitigation, and long-term viability in a rapidly shifting EV market.

As EV demand cycles fluctuate and policy frameworks evolve, the industry must move beyond headline gigafactory announcements and confront the harder question: what battery manufacturing models are economically, operationally, and strategically sustainable?

This session offers a rare, pragmatic perspective on scaling domestic battery production in today’s volatile market.

• Evaluate the real economic drivers of domestic cell production, including yield, scrap, formation, and capital expenditure impacts on $/kWh.

• Assess the risks and benefits of outsourcing vs full domestic manufacturing, particularly in volatile demand environments.

• Understand how IRA incentives influence production strategy, investment timing, and supply chain configuration.

• Identify operational bottlenecks in scaling from pilot to gigafactory, including automation, workforce, and process stability.

• Develop a realistic framework for determining what battery manufacturing models are truly scalable in North America.

Gigafactory Reality: Achieving Yield, Quality & Cost Targets in Battery Pack Manufacturing

Gigafactory scale is no longer the challenge — consistent, high-yield production is. While capacity announcements continue to grow, many operations are still constrained by scrap rates, process variability, rework, and quality escapes that directly impact cost and throughput.

At pack level, complexity increases further. Cell variation, module/pack assembly tolerances, joining processes, thermal interface application, and end-of-line validation all introduce yield loss mechanisms that are often underestimated at design stage.

This session delivers a practical, engineering-led view of what it takes to achieve stable yield, consistent quality, and competitive $/kWh in battery pack manufacturing. It examines how OEMs and suppliers are managing process control, reducing variability, and designing for manufacturability across high-volume production environments.

Rather than focusing on theoretical capacity, the discussion centres on the real operational drivers of yield and cost, and how small inefficiencies at scale translate into significant financial impact.

As the industry moves from pilot to full-rate production, execution — not design — has become the primary differentiator.

This session offers a clear, pragmatic view of how to deliver battery packs at scale, with the yield, quality, and cost performance required for commercial success.

• Understand the primary drivers of yield loss in battery pack manufacturing, including process variability, assembly tolerances, and material handling.

• Evaluate how design for manufacturability (DfM) impacts scrap rates, rework, and overall production efficiency.

• Assess the role of process control, in-line inspection, and data feedback loops in maintaining consistent quality at scale.

• Identify key cost drivers at pack level, including labour, automation, cycle time, and defect rates.

• Develop a practical framework for achieving stable, high-quality, and cost-effective battery pack production.

AI-Driven Engineering for Next-Generation EV Battery Systems

TBC – Neural Concept

As EV battery systems grow larger, more structural, and more thermally complex, traditional CAE workflows are struggling to keep pace. Full finite element simulations for crash, thermal, and structural validation can take hours or days per iteration — limiting design exploration and slowing development cycles.

AI-driven surrogate modeling is changing that equation.

This session explores how deep learning models trained on physics-based simulations are enabling engineers to predict structural and thermal performance in milliseconds — unlocking rapid design iteration, broader optimisation, and earlier risk identification across battery pack architectures.

• Understand how AI surrogate models can replicate physics-based simulations with significant speed gains

• Evaluate the application of real-time structural prediction for battery enclosure crash performance

• Assess how AI-driven workflows accelerate thermal and pack-level optimisation

• Identify opportunities to integrate generative design and multi-physics modelling into battery development pipelines

• Quantify how simulation acceleration reduces development risk, cost, and time-to-production

AI in Battery Development: Where It Actually Works
Moving Beyond the Hype to Deliver Real Engineering Value

Software-Defined Batteries: Using AI, Data, and Adaptive Control to Optimise Performance, Safety and Lifetime Across EV Fleets

Hardware innovation alone can no longer deliver the performance, safety, and lifetime required by modern EV programmes. The next frontier is the software-defined battery, where AI-driven battery management systems, predictive thermal control, and adaptive charging algorithms dynamically optimise battery behaviour throughout its lifecycle. This session explores how next-generation BMS architectures—leveraging machine learning, digital twins, and fleet-wide telemetry—are enabling OEMs to improve charging performance, extend battery life, enhance safety, and unlock continuous optimisation through software.

• Understanding how AI-driven battery management systems are transforming battery control beyond traditional rule-based architectures.

• Exploring predictive thermal management strategies that dynamically optimise battery temperature and performance in real time.

• Examining adaptive charging algorithms that balance ultra-fast charging capability with long-term battery health and degradation mitigation.

• Learning how OEMs are leveraging fleet-wide battery telemetry and cloud analytics to improve diagnostics, lifetime prediction, and software optimisation across deployed vehicles.

• Identifying the data infrastructure, validation frameworks, and cybersecurity considerations required to safely deploy software-defined battery architectures at scale.

Networking Break

AI-Driven Battery Lifetime Modelling: What Can We Actually Predict?

Accurately predicting battery lifetime remains one of the most difficult challenges in EV development. Degradation is driven by coupled electrochemical, thermal, and usage-dependent factors, making real-world performance highly variable and difficult to model with confidence.

Traditional lifetime models — based on lab testing and conservative assumptions — often fail to capture this complexity at fleet scale. As a result, OEMs face uncertainty in durability targets, charging strategies, and warranty exposure.

This session examines how AI-driven modelling is being applied to improve degradation prediction and battery lifetime forecasting. By combining fleet telemetry, machine learning, and physics-based models, engineers are developing more accurate tools to understand ageing pathways and predict state-of-health under real-world conditions.

The focus is on the practical application of AI in lifetime modelling — where it improves predictive accuracy, enables optimisation of charging and usage strategies, and reduces uncertainty in long-term performance.

Rather than positioning AI as a replacement for traditional models, the discussion explores how hybrid approaches are being used to deliver more reliable, scalable lifetime predictions.

This session offers a clear, engineering-led view of how AI is being used to model battery degradation and improve EV battery performance over time.

• Understand the key drivers of battery degradation and why they are difficult to model using traditional approaches.

• Evaluate how AI and machine learning improve lifetime prediction through the use of fleet data and real-world operating conditions.

• Assess how hybrid modelling approaches combine physics-based models with data-driven techniques to increase accuracy.

• Identify how lifetime modelling informs charging strategies, performance optimisation, and warranty risk management.

• Develop a practical framework for deploying AI-driven lifetime models within EV development and validation processes.

Battery Data Analytics: What Are We Actually Learning from Fleet Data?

Achieving Ultra-Fast Charging Without Destroying Battery Life

Ultra-fast charging is now a core requirement for EV adoption — but pushing charge rates toward 350–500kW introduces failure mechanisms that directly impact battery life, safety, and warranty exposure. Lithium plating, accelerated degradation, and thermal stress are no longer edge cases; they are primary engineering constraints.

The challenge is not enabling peak charge rates, but sustaining fast charging performance without compromising long-term durability. Charge profiles, thermal conditions, cell design, and BMS control strategies must all operate within tightly managed limits to avoid irreversible damage.

This session provides a practical, engineering-led examination of how OEMs and cell developers are balancing charging speed with battery longevity. It explores how advanced charge control algorithms, thermal pre-conditioning, and cell-level design optimisation are being used to mitigate plating risk and manage degradation under high C-rate conditions.

The focus is on the trade-offs between charging performance and lifecycle durability, and how these are being managed in real-world vehicle platforms.

Rather than focusing on headline charging speeds, the discussion centres on what it takes to deliver consistent, repeatable fast charging without increasing warranty risk or reducing usable battery life.

This session offers a clear, pragmatic view of how ultra-fast charging can be achieved without compromising long-term battery performance.

• Understand the key degradation mechanisms associated with ultra-fast charging, including lithium plating and thermal stress.

• Evaluate how charge control strategies and BMS algorithms manage risk at high C-rates.

• Assess the role of thermal management and pre-conditioning in enabling safe, repeatable fast charging.

• Identify cell design and chemistry considerations that support higher charge rates with minimal degradation.

• Develop a practical framework for balancing charging speed, performance, and battery lifetime.

800V–1000V Architectures: What Actually Changes at High Voltage?

As OEMs transition from 400V to 800V and beyond, high-voltage architectures are becoming essential to enable ultra-fast charging, reduce current loads, and improve drivetrain efficiency. However, increasing system voltage introduces a new set of engineering constraints that extend far beyond simple scaling.

Higher voltages place greater demands on insulation systems, dielectric materials, and component spacing, while increasing the risk of partial discharge, arcing, and long-term degradation. At the same time, thermal behaviour, switching performance, and system-level efficiency must be carefully managed across power electronics, cabling, and battery pack design.

This session provides a practical, engineering-led examination of how high-voltage battery systems are being designed and integrated into next-generation EV platforms. It explores how OEMs are addressing insulation coordination, material selection, safety strategies, and packaging constraints under higher electrical stress.

The focus is on the trade-offs between performance, safety, and reliability when operating at 800V–1000V, and what this means for system design, validation, and long-term durability.

Rather than focusing on voltage as a headline figure, the discussion centres on the real engineering implications of moving to high-voltage architectures.

This session offers a clear, pragmatic view of how to design and deliver high-voltage battery systems that perform reliably at scale.

• Understand the key challenges introduced by 800V–1000V systems, including insulation, dielectric stress, and electrical safety risks.

• Evaluate how high voltage impacts thermal behaviour, switching performance, and overall system efficiency.

• Assess material selection and design strategies for managing partial discharge, arcing, and long-term degradation.

• Identify integration challenges across battery packs, power electronics, and vehicle architecture.

• Develop a practical framework for designing safe, reliable, and high-performance high-voltage battery systems.

Battery Aging & Degradation: What Actually Drives Lifetime Performance?

Battery lifetime remains one of the least predictable aspects of EV performance. Degradation is driven by coupled electrochemical, thermal, and usage-dependent factors, making real-world ageing highly variable and difficult to model with confidence.

Laboratory testing and standard cycle profiles often fail to capture the complexity of field conditions — including fast charging behaviour, temperature variation, and diverse duty cycles — leading to gaps between expected and actual performance.

This session provides a practical, engineering-led examination of the real drivers of battery degradation. It explores how engineers are combining electrochemical modelling, real-world usage data, and machine learning analytics to better understand ageing mechanisms and improve lifetime prediction.

The focus is on the interaction between chemistry, operating conditions, and usage patterns, and how these influence capacity fade, resistance growth, and long-term reliability.

Rather than relying on simplified assumptions, the discussion centres on how to build more accurate, data-informed models that reflect real-world behaviour.

This session offers a clear, pragmatic view of how to understand, predict, and manage battery degradation in next-generation EV platforms.

• Understand the primary mechanisms driving battery ageing, including lithium plating, SEI growth, and thermal effects.

• Evaluate the limitations of traditional lifetime testing and modelling approaches.

• Assess how real-world usage data improves understanding of degradation behaviour.

• Identify how electrochemical models and machine learning can be combined to enhance prediction accuracy.

• Develop a practical framework for improving battery lifetime prediction and durability performance.

Why Battery Packs Fail in the Field: Understanding Real-World Failure Mechanisms in EV Battery Systems

Despite extensive laboratory validation and compliance testing, many EV battery failures only emerge once vehicles are deployed in real-world operating environments. Variations in usage patterns, environmental conditions, and charging behaviour can expose weaknesses that are difficult to replicate during development testing.

This session examines the most common root causes of field failures in EV battery packs, including cell mismatch, thermal gradients within densely packaged systems, BMS calibration errors, and accelerated degradation caused by repeated fast charging. By analysing real-world performance data and failure investigations, experts will explore how these mechanisms interact to create safety risks, performance loss, and warranty exposure. The discussion will highlight how improved pack design, thermal management strategies, more accurate battery management algorithms, and better validation methodologies can reduce failure risk and improve long-term reliability across large EV fleets.

• Understand the most common root causes of field failures, including cell imbalance, thermal gradients, and BMS calibration issues.

• Evaluate how real-world usage patterns and environmental conditions drive degradation and failure.

• Assess the limitations of current validation and testing methodologies in predicting field performance.

• Identify how interacting failure mechanisms propagate at pack level to create safety and reliability risks.

• Develop a practical framework for improving pack design, validation, and operational strategies to reduce field failures.

Warranty Risk in EV Batteries: Predicting Failure Before It Becomes a Cost

As EV fleets scale globally, battery warranties are emerging as one of the most significant financial risks facing automakers. While laboratory testing and validation programmes are designed to characterise degradation and ensure compliance with performance targets, real-world vehicle usage often introduces operating conditions that differ significantly from controlled test environments. This session examines how real-world degradation patterns, charging behaviour, thermal exposure, and duty cycles influence long-term battery performance and warranty exposure. Experts will explore the gap between traditional abuse testing methodologies and real-world usage scenarios, and how OEMs are developing more predictive approaches to identify early signs of failure before they lead to costly field issues. By combining advanced diagnostics, fleet telemetry, and predictive modelling, manufacturers are working to detect emerging failure modes earlier, improve durability forecasting, and reduce the long-term financial risk associated with EV battery warranties.

• Understand the key drivers of battery warranty risk, including degradation variability, usage patterns, and environmental factors.

• Evaluate the gap between laboratory validation and real-world performance in predicting long-term reliability.

• Assess how diagnostics, fleet telemetry, and predictive models can identify early signs of failure.

• Identify how degradation and failure mechanisms translate into warranty cost and financial exposure.

• Develop a practical framework for reducing warranty risk through improved prediction, monitoring, and design strategies.

Battery Recyclability & Design for Disassembly: Engineering EV Battery Packs for Circularity

Chair’s Closing Remarks

Designing Battery Packs for Serviceability and Repair

As EV fleets scale, battery repairability is becoming an operational and financial constraint. Highly integrated architectures — including structural packs and cell-to-pack designs — reduce part count and improve performance, but often make inspection, access, and repair significantly more difficult.

Traditional service models are no longer directly applicable. Limited access to cells, permanent joining methods, and tightly integrated thermal and structural systems increase repair complexity, cost, and downtime — often pushing packs toward full replacement rather than targeted repair.

This session provides a practical, engineering-led examination of how OEMs are addressing serviceability within next-generation battery designs. It explores how access strategies, modular substructures, diagnostic capabilities, and reversible joining methods are being used to enable repair without compromising structural integrity or safety.

The focus is on the trade-offs between integration, performance, and serviceability, and how these impact lifecycle cost, warranty strategy, and field operations.

Rather than treating service as an afterthought, the discussion centres on how early design decisions determine whether packs can be repaired — or only replaced.

This session offers a clear, pragmatic view of how to design battery systems that can be maintained in real-world conditions.

• Understand how highly integrated pack architectures impact serviceability, repair time, and cost.

• Evaluate design strategies for enabling access, modular repair, and component replacement.

• Assess the role of diagnostics and BMS data in identifying repairable faults.

• Identify trade-offs between structural integration, safety, and field service requirements.

• Develop a practical framework for designing battery packs that support efficient repair and maintenance.