scieee AI-readable full text Open interactive document viewer

Modular battery pack design and serviceability in electric vehicles

Adebowale, Oluwapelumi Joseph

Abstract

The rapid growth of electric vehicles (EVs) has heightened the demand for battery systems that not only deliver high performance but are also efficient to maintain, scale, and recycle. While much of the industry’s focus has been on energy density and cost optimization, serviceability—defined by ease of maintenance, diagnostic accessibility, and component-level replacement—has emerged as a critical yet underprioritized factor. Traditional EV battery packs, often monolithic and tightly integrated, pose significant challenges for field technicians, including prolonged disassembly times, high-voltage safety risks, and limited diagnostic transparency. These limitations increase downtime, escalate service costs, and constrain the long-term sustainability of EV platforms. This paper explores the transformative role of modular battery pack design in improving serviceability and lifecycle efficiency across EV ecosystems. From a broader perspective, it examines how modularity facilitates streamlined maintenance workflows, safer handling procedures, and standardized replacement strategies. The analysis narrows to compare the design philosophies of leading OEMs such as Tesla, GM, Rivian, and Lucid, evaluating how different architectures impact field repairability and technician safety. Further sections explore the ripple effects of modular design on manufacturing automation, second-life reuse, and end-of-life disassembly for recycling. Emphasis is also placed on interface standardization, diagnostic system integration, and the need for interoperable service protocols. A real-world case study demonstrates how design decisions—such as interlock logic, balancing procedures, and module accessibility—translate into measurable service efficiency improvements. The paper concludes with strategic recommendations for advancing modular, service-oriented battery pack architectures that align with the evolving demands of sustainable, technician-friendly EV platforms.

Full text

 Corresponding author: Oluwapelumi Joseph Adebowale Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Modular battery pack design and serviceability in electric vehicles Oluwapelumi Joseph Adebowale * Department of Mechanical Engineering, Purdue University, USA. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 Publication history: Received on 02 April 2025; revised on 11 May 2025; accepted on 13 May 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.1902 Abstract The rapid growth of electric vehicles (EVs) has heightened the demand for battery systems that not only deliver high performance but are also efficient to maintain, scale, and recycle. While much of the industry’s focus has been on energy density and cost optimization, serviceability—defined by ease of maintenance, diagnostic accessibility, and componentlevel replacement—has emerged as a critical yet underprioritized factor. Traditional EV battery packs, often monolithic and tightly integrated, pose significant challenges for field technicians, including prolonged disassembly times, highvoltage safety risks, and limited diagnostic transparency. These limitations increase downtime, escalate service costs, and constrain the long-term sustainability of EV platforms. This paper explores the transformative role of modular battery pack design in improving serviceability and lifecycle efficiency across EV ecosystems. From a broader perspective, it examines how modularity facilitates streamlined maintenance workflows, safer handling procedures, and standardized replacement strategies. The analysis narrows to compare the design philosophies of leading OEMs such as Tesla, GM, Rivian, and Lucid, evaluating how different architectures impact field repairability and technician safety. Further sections explore the ripple effects of modular design on manufacturing automation, second-life reuse, and end-of-life disassembly for recycling. Emphasis is also placed on interface standardization, diagnostic system integration, and the need for interoperable service protocols. A real-world case study demonstrates how design decisions—such as interlock logic, balancing procedures, and module accessibility—translate into measurable service efficiency improvements. The paper concludes with strategic recommendations for advancing modular, serviceoriented battery pack architectures that align with the evolving demands of sustainable, technician-friendly EV platforms. Keywords: Modular Battery Design; EV Serviceability; Diagnostic Accessibility; Field Maintenance; Battery Pack Architecture; Electric Vehicle Sustainability 1. Introduction 1.1. Rise of Electric Vehicles (EVs) and Importance of Battery Pack Design The global automotive industry is undergoing a transformative shift, with electric vehicles (EVs) positioned at the center of a sustainable transportation revolution. In response to tightening emissions regulations, technological advancements, and growing consumer demand for cleaner alternatives, EV adoption has surged over the past decade [1]. Major automakers are reconfiguring their product strategies to prioritize battery electric vehicles (BEVs) over internal combustion engine (ICE) platforms, with forecasts indicating that EVs could represent over 50% of new vehicle sales globally by 2040 [2]. Central to the functionality, performance, and longevity of EVs is the battery pack—comprising modules, cells, and an intricate network of sensors, cooling systems, and structural housings. The battery is not only the most expensive World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2206 component of the EV powertrain but also the most technically complex and safety-critical [3]. As such, its design has profound implications for vehicle performance, charging behavior, weight distribution, and crashworthiness. Traditionally, battery pack design has been dominated by performance-centric metrics such as energy density, power output, and thermal management efficiency. However, as EVs enter mainstream markets and ownership cycles extend beyond initial warranty periods, design priorities are evolving to include ease of service, diagnostics, and modularity [4]. These considerations are essential for reducing lifecycle costs, supporting circular economy goals, and enabling second-life applications such as energy storage [5]. In this context, the serviceability of EV battery packs—defined as the ease with which they can be diagnosed, accessed, removed, repaired, or replaced—is becoming an increasingly critical metric in both engineering and economic evaluations. Battery pack design decisions must therefore balance performance objectives with long-term operational accessibility and safety, particularly as global EV fleets continue to scale [6]. 1.2. Strategic Shift from Performance-First to Serviceability-Aware Design The earliest generations of EVs prioritized rapid innovation in energy storage, focusing heavily on maximizing range, minimizing weight, and ensuring thermal stability. While these design imperatives were justified by technological immaturity and market competitiveness, they often resulted in battery architectures that were tightly integrated, inaccessible, and difficult to repair without specialized tools or complete pack replacement [7]. Today, as the EV industry matures, manufacturers are recognizing the strategic value of serviceability-aware design. This design paradigm shifts the emphasis from short-term performance metrics to lifecycle operability, safety, and costeffectiveness. It includes considerations such as modular pack construction, accessible fasteners, integrated diagnostic sensors, and standardized interfaces for disassembly and testing [8]. Such features enable routine maintenance, reduce technician training time, and facilitate rapid response to battery faults—thereby enhancing the resilience of EV service networks. Furthermore, increasing scrutiny from regulators, fleet operators, and insurance providers is amplifying the need for transparent, serviceable battery designs. Policies around right-to-repair, extended product responsibility, and end-oflife material recovery require that battery systems be designed for traceability and safe deconstruction [9]. Failure to address these needs may result in financial penalties, reputational risk, and reduced competitiveness in aftermarket services. Companies like Tesla, Ford, and Volkswagen have begun incorporating modular battery platforms with serviceability in mind, allowing technicians to replace individual modules instead of entire packs. This practice reduces environmental impact and lowers warranty repair costs while maintaining customer trust [10]. Additionally, design for serviceability supports emerging business models such as battery leasing and energy repurposing, creating new revenue streams beyond the initial vehicle sale. By embracing this shift, manufacturers can future-proof their EV platforms, align with sustainability goals, and support a more robust and technician-friendly service ecosystem [11]. 1.3. The Cost of Poor Serviceability: Technician Risk, Downtime, Customer Satisfaction Poor serviceability in EV battery packs carries significant financial, operational, and safety implications. One of the most pressing concerns is technician risk. High-voltage battery systems can pose serious hazards—including electric shock, thermal runaway, and chemical exposure—if proper procedures and safety mechanisms are not integrated into the design [12]. Battery packs that are sealed, inaccessible, or lack diagnostic clarity force technicians to conduct timeconsuming and potentially hazardous disassembly procedures, increasing the likelihood of accidents or improper handling. Secondly, poor serviceability directly contributes to vehicle downtime. In commercial fleets or rideshare operations, prolonged battery servicing can translate to lost revenue, increased operational costs, and logistical bottlenecks. The inability to diagnose and address battery issues quickly impairs overall fleet availability and disrupts maintenance workflows [13]. From the consumer perspective, customer satisfaction is closely linked to service experience. Long wait times, high repair costs, and unclear diagnosis of battery faults can erode brand loyalty and drive negative perceptions about EV World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2207 ownership. Unlike ICE vehicles, where repair and maintenance ecosystems are well-established, EV service networks are still emerging—and poor battery accessibility compounds this challenge [14]. Additionally, the inability to efficiently replace or upgrade battery modules undermines the potential for second-life applications, battery recycling, and warranty compliance. These inefficiencies escalate total cost of ownership (TCO) and work against industry-wide sustainability goals [15]. Addressing these issues through serviceability-conscious design is not just a technical concern—it is a strategic imperative that affects safety, efficiency, customer satisfaction, and long-term brand viability. 1.4. Preview of Article Structure This article explores how battery pack design in electric vehicles must evolve to prioritize serviceability without compromising performance. Section 2 provides a technical overview of battery architectures and the relationship between pack layout and repair complexity. Section 3 examines real-world service challenges through field data and technician case studies. Section 4 presents design principles and emerging technologies aimed at improving serviceability. Section 5 outlines regulatory trends and business model implications, while Section 6 offers recommendations for industry stakeholders. The conclusion synthesizes findings to propose a roadmap for integrating serviceability into next-generation EV design strategies [16]. 2. Design for serviceability and maintenance efficiency 2.1. Challenges in Servicing EV Battery Packs Servicing electric vehicle (EV) battery packs presents a unique set of challenges, stemming primarily from the physical characteristics and safety requirements of high-energy systems. The most immediate concern is high-voltage risk. Most EV packs operate between 400 to 800 volts, with some performance vehicles exceeding 900 volts. Contact with improperly isolated components can result in lethal electric shocks, requiring technicians to use specialized personal protective equipment (PPE), insulated tools, and high-voltage training certification [6]. Another hazard arises from thermal risks. Damaged or degraded cells can initiate thermal runaway, a self-propagating chemical reaction that leads to fires or explosions. The presence of volatile electrolytes within densely packed modules elevates this risk during disassembly, especially when pressure release valves or thermal fuses are inaccessible [7]. Improper cooling line disconnection, punctured casings, or improper handling can result in dangerous outcomes even during routine servicing. A critical technical hurdle is disassembly complexity. Many early-generation packs are designed for durability and compactness, often relying on potted resin encapsulation or welded seams that are difficult to reverse in the field. This not only lengthens service time but also increases the likelihood of damage during teardown procedures [8]. Some pack configurations bury modules beneath structural components, requiring full underbody access or hoisting systems, complicating mobile or field servicing efforts. Further complexity arises from architectural variation across manufacturers. Cell types (pouch, cylindrical, prismatic), cooling layouts (plate, immersion, or serpentine tube), and control systems vary widely, leaving technicians with inconsistent training frameworks and diagnostic tooling [9]. Without standardization, identifying fault location or root causes is time-intensive and error-prone. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2208 Figure 1 Cross-sectional diagram of conventional vs. modular pack service pathways Additionally, many EV packs suffer from diagnostic uncertainty. Battery Management Systems (BMS) often provide limited or encrypted fault codes. Without transparent diagnostics or cell-level monitoring, technicians must rely on inefficient trial-and-error replacement strategies, which inflate service costs and compromise efficiency [10]. 2.2. Advantages of Modular Designs Modular battery pack design introduces a paradigm shift in the way serviceability, scalability, and sustainability are approached in EV engineering. A modular design consists of independently accessible and detachable units—typically sub-packs or cells—housed within a common frame. This configuration offers a wide range of benefits, especially in terms of maintenance and long-term operational efficiency. Ease of access is among the most compelling advantages. Instead of requiring full pack removal or deconstruction, modular packs allow technicians to isolate and service defective modules quickly. Service panels, snap-in fasteners, and external harness connectors reduce the need for invasive pack disassembly and limit technician exposure to highvoltage circuits [11]. Furthermore, modular layouts support tool-less diagnostics in some systems, with embedded fault LEDs and programmable sensor outputs facilitating rapid inspection. This accessibility leads directly to reduced downtime. In fleet operations, logistics, and public transit systems, vehicle uptime is a mission-critical parameter. Modular battery architecture allows for same-day module replacement and reduces the need to offload vehicles to service centers. This agility is particularly beneficial for mobile service units deployed in remote or high-turnover regions [12]. Another benefit lies in lower training requirements. Instead of training technicians on full-pack architecture and teardown protocols, manufacturers can develop modular training modules focused on common fault scenarios, connector management, and cell isolation techniques. This reduces onboarding time, standardizes safety procedures, and lowers labor costs over time [13]. A modular system also supports isolated module replacement rather than full-pack service. This is critical in managing warranty costs, as OEMs and third-party warranty providers often face financial strain replacing entire packs for faults isolated to a single cell cluster. Targeted repairs lower material use, reduce environmental impact, and extend pack lifecycles—contributing to circular economy goals [14]. From a field maintenance perspective, modularity supports flexible deployment. Technicians can carry replacement modules, test kits, and standardized tools, minimizing the need for full-shop infrastructure. Moreover, modular designs facilitate quick diagnostics and allow for proactive replacement strategies in vehicles with predicted module-level degradation. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2209 Table 1 Comparative Metrics – Disassembly Time, Service Cost, and Technician Hazard Level Pack Architecture Disassembly Time (min) Service Cost (USD) Technician Hazard Level<br>(0–5) Remarks Fully Modular 30–45 400–800 1.5 Fast access; low-voltage isolation zones; supports part-level repairs. Semi-Modular 60–90 800–1,200 2.5 Mixed access paths; partial automation; risk varies by configuration. Integrated (Welded) 120–180 1,500– 2,200 4.0 Difficult teardown; higher voltage exposure; full-pack handling required. Potted/Sealed >180 >2,500 4.5 Destructive process; thermal and chemical hazards; non-reversible disassembly. Quantitatively, modular designs exhibit superior performance in key service metrics. Studies have shown disassembly times reduced by up to 60%, service costs lowered by 40%, and technician hazard exposure significantly mitigated compared to monolithic pack layouts [15]. Finally, modularity supports revenue continuity and reputation. Faster service cycles reduce customer frustration, support service-level agreements (SLAs), and reduce loaner vehicle costs. For OEMs, this translates into enhanced postsale engagement, lower net warranty liabilities, and the ability to offer premium service tiers based on faster, more reliable battery care [16]. 2.3. OEM Approaches to Modular Serviceability Different EV manufacturers have taken divergent approaches to battery pack design, each balancing modularity, integration, cost, and manufacturability. These approaches reflect trade-offs between performance optimization and long-term serviceability. Tesla’s battery architecture is renowned for its energy density and structural integration. In the Model S and Model 3, Tesla utilizes tightly packed cylindrical cells within a bonded and potted structure. This configuration enhances thermal and structural performance but poses major serviceability challenges [17]. The pack is difficult to open without specialized tools, and module replacement is rarely viable outside centralized service hubs. Moreover, Tesla limits thirdparty access to diagnostic interfaces, restricting service to certified centers. While this allows for quality control, it reduces flexibility and raises ownership costs for out-of-warranty customers [18]. In contrast, Rivian’s R1T and R1S platforms emphasize ruggedness and field maintainability. The company uses a stackable modular configuration where sub-packs can be accessed through removable panels. Diagnostic ports are externalized, and module identification labels are visible without disassembly. These design decisions align with Rivian’s customer base—off-road users and fleet operators—who value service flexibility in decentralized locations [19]. General Motors (GM) introduced the Ultium battery platform, which represents a balance between modularity and manufacturing efficiency. Ultium utilizes large-format pouch cells arranged in replaceable modules within a scalable matrix. Each module is individually cooled and monitored, with connectors designed for rapid disconnection. GM’s platform also features a unified BMS capable of module-level voltage and thermal reporting, allowing granular diagnostics. This design supports both performance optimization and field-level module replacement, making it one of the most serviceable high-capacity systems currently in mass production [20]. Lucid Motors, with its Air luxury sedan, has adopted a semi-serviceable architecture. Lucid’s pack consists of highdensity cylindrical cells housed in “smart modules” with embedded diagnostics and voltage balancing. Although the pack is sealed with a structural enclosure for stiffness and crash safety, the modules are accessible via a guided removal process. Lucid has partnered with certified technicians and provides cloud-linked diagnostics for remote fault detection. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2210 While less modular than Rivian or GM, Lucid’s architecture supports tiered service workflows and prioritizes safety in handling [21]. Figure 2 Exploded-view comparison of battery pack modularity across OEMs Table 2 OEM Modularity Scores — Accessibility, Diagnostic Interface, Part-Level Repairability OEM Accessibility (0–5) Diagnostic Interface (0– 5) Part-Level Repairability (0– 5) Total Score (0–15) Remarks Tesla 2 2 1 5 Highly integrated design; limited third-party diagnostics; low modular serviceability. Rivian 5 4 4 13 Rugged modular layout; accessible panels; good BMS data access. GM (Ultium) 4 5 4 13 Strong module-level diagnostics and fieldserviceable modules. Lucid 3 4 3 10 Semi-serviceable smart packs; decent diagnostic clarity. Ford 4 3 3 10 Modular design across platforms; moderate interface transparency. Hyundai/Kia 3 3 2 8 Pack segmentation exists; limited BMS openness; service strategy evolving. Volkswagen 4 3 3 10 ID series offers moderate serviceability and growing diagnostic capabilities. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2211 Table 2 scores OEM platforms on modularity based on three core dimensions: physical accessibility, diagnostic interface transparency, and feasibility of part-level repairability. Rivian and GM score highest across all categories, while Tesla scores lowest in serviceability despite technological sophistication [22]. OEM decisions around modularity are shaped not only by technical feasibility but also by brand strategy, repair ecosystem philosophy, and post-sale monetization models. Manufacturers who prioritize customer experience, fleet serviceability, and circular economy alignment tend to invest more heavily in modularity and open diagnostics. As the EV market matures, industry momentum is shifting toward standardized modularity benchmarks. Collaborative initiatives between OEMs, regulators, and service providers may soon codify minimum serviceability standards— further pressuring automakers to reconsider their design choices in favor of technician safety, efficiency, and long-term cost control [23]. 3. Impact of modular design on manufacturing, scalability, and recycling 3.1. Manufacturing and Automated Assembly The industrialization of electric vehicle (EV) battery production has prioritized automation, standardization, and throughput efficiency. In this context, modular battery pack architectures present unique advantages for manufacturing and robotic assembly, especially when compared to fully integrated designs. Modular packs often use repeatable substructures, such as standardized trays, busbar arrangements, and coolant manifolds, that can be produced and assembled in a robot-friendly sequence [11]. The emergence of cell-to-pack (CTP) and module-to-pack (MTP) strategies has further streamlined production processes. CTP design eliminates intermediate module casings and places cells directly into the pack housing, enhancing energy density and reducing material use. MTP configurations maintain modular benefits while preserving efficient sub-pack integration, allowing manufacturers to strike a balance between serviceability and performance [12]. These architectures reduce the number of individual welds, connectors, and fasteners—each of which adds complexity and cost in automated environments. One of the key enablers of automation is dimensional consistency. Modular systems often employ precisely aligned cell arrays, compatible with robotic stacking, adhesive application, and torquing procedures. This repeatability supports high-throughput assembly lines while maintaining tight tolerances required for thermal management and safety [13]. Despite these advantages, trade-offs remain. Greater modularity often requires additional mechanical enclosures, interconnects, and redundant cooling pathways, which can slightly reduce gravimetric energy density. For highperformance vehicles or long-range applications, these compromises can affect overall vehicle range or require upsizing of the battery footprint [14]. To address this, advanced OEMs use hybrid techniques such as smart modularization, where only failure-prone zones are designed for disassembly, while low-risk zones are optimized for integration. These hybrid approaches retain the benefits of modular manufacturing while preserving energy density targets [15]. Ultimately, the compatibility of modular pack designs with automated assembly systems enhances manufacturability, reduces labor dependency, and enables faster product iteration cycles, making them highly attractive for modern gigafactory environments. 3.2. Scalability and Platform Flexibility One of the most strategically important advantages of modular battery architecture is its potential for scalability and cross-platform flexibility. In the era of vehicle electrification, automakers are moving toward "design once, deploy many" platforms, where a single battery system can power multiple vehicle types—from sedans to SUVs to delivery vans—with minimal modification [16]. Modular packs make this possible by allowing variable stack configurations. OEMs can increase pack capacity by adding more modules or achieve weight savings by reducing the module count—all while maintaining consistent interface geometries and electronic control protocols. For instance, General Motors' Ultium platform uses a standardized cell format and pack structure across dozens of vehicle models, minimizing development lead time and production line complexity [17]. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2212 This standardization also simplifies logistics and inventory management. A modular architecture enables automakers and service centers to stock a common set of replacement modules and connectors instead of bespoke parts for each vehicle model. This consolidation reduces warehouse footprint, improves parts availability, and streamlines global service supply chains [18]. From a product development perspective, modularity supports parallel engineering. Battery teams can develop modules and packs concurrently with vehicle chassis designers, reducing the need for redesign when vehicle parameters evolve. This accelerates time-to-market and lowers the risk of costly mid-cycle adjustments [19]. Moreover, flexible battery packs facilitate the integration of different cell chemistries (e.g., NMC, LFP) or form factors (e.g., pouch, prismatic) for regional customization or cost optimization. This adaptability is particularly valuable for automakers selling across markets with varying environmental conditions, subsidy schemes, and performance expectations [20]. However, achieving such flexibility requires deliberate architectural planning. The mechanical, thermal, and electrical interfaces of modules must be designed for interoperability, often requiring complex simulation and validation to ensure that packs perform reliably across configurations. Despite the engineering overhead, the long-term economic and logistical gains of scalable modular systems make them a compelling design strategy [21]. Thus, modular battery platforms offer a foundation for cost-effective product diversification, inventory optimization, and consistent service delivery—critical factors in a competitive and fast-evolving EV market. 3.3. Recycling and Second-Life Applications Battery end-of-life (EOL) management is an urgent priority as EV adoption scales globally. Modular battery architectures offer significant advantages for both recycling and second-life applications, particularly by enabling safer, faster, and more efficient pack disassembly and materials recovery. One of the primary benefits of modularity is ease of module-level testing. Before recycling, battery packs are often evaluated for second-life use in stationary energy storage, grid balancing, or microgrid systems. Modular designs allow technicians to isolate and test individual modules for state of health (SOH), internal resistance, and capacity retention. Modules that meet performance thresholds can be redeployed, while degraded ones are directed to material recovery processes [22]. In contrast, integrated packs often require destructive disassembly or yield inconsistent module integrity, reducing reuse potential and increasing hazardous waste. Modular systems simplify this triage process, supporting circular economy objectives and reducing the carbon footprint of battery production through reuse [23]. Design also impacts end-of-life sorting and dismantling efficiency. Modular packs with standard fasteners, labeled harnesses, and separable components can be dismantled by semi-automated systems, reducing labor costs and technician exposure to toxic materials. In contrast, integrated packs often rely on adhesives, welds, or proprietary seals, complicating automation and increasing environmental hazard risks [24]. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2213 Figure 3 Flow diagram – battery life cycle in modular vs. integrated systems From a materials perspective, modularity enables cleaner separation of high-value materials such as cobalt, nickel, and copper. Packs designed for recyclability use dissimilar material junctions, coating indicators, and tool-readable QR codes to improve traceability and automation compatibility in dismantling lines [25]. Table 3 Recyclability Metrics – Time, Automation Compatibility, Material Recovery Rate Pack Type Average Disassembly Time (min) Automation Compatibility<br> (0– 5) Material Recovery Rate (%) Remarks Modular (Highend) 25–40 4.5 85–90 Fast disassembly with standardized fasteners; suitable for robotic sorting and recovery. Modular (Standard) 45–60 3.5 75–85 Requires semi-automated processes; some manual intervention still necessary. Semi-Modular 60–90 2.5 60–75 Mixed interfaces; adhesives and limited standardization increase processing time. Integrated 120–180 1.5 40–55 Adhesives, welded joints, and unclear separation paths hinder dismantling and recovery. Potted/Sealed >180 0.5 <40 Destructive disassembly often required; minimal automation potential and high waste. Table 3 presents key recyclability metrics across modular and integrated pack designs. Metrics include average disassembly time, compatibility with automated extraction systems, and total recoverable material mass. Modular designs consistently outperform integrated architectures, particularly in automation readiness and safe handling scores [26]. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2220 In totality, the vision for future modular battery systems is one where design, diagnostics, and field execution are seamlessly unified—paving the way for a safer, smarter, and more sustainable electrified transportation ecosystem. 7. Conclusion The evolution of electric vehicle (EV) battery systems has rightly prioritized energy density, power efficiency, and thermal stability. However, as EV adoption matures and vehicles reach broader markets, another dimension is rising to equal strategic importance: serviceability. This study has demonstrated that modular battery pack design is not merely a structural convenience—it is a transformative enabler of safer, faster, and more cost-effective field servicing. Through modular configurations, technicians gain improved access, diagnostic clarity, and operational confidence, while manufacturers benefit from reduced downtime, enhanced brand trust, and scalable maintenance infrastructures. Modular battery packs empower service networks to isolate faults quickly, swap components without full-pack replacement, and implement targeted interventions rather than resorting to labor-intensive disassembly. These advantages extend beyond individual repairs. They reshape warranty economics, support emerging reuse markets, and strengthen the long-term sustainability of EV platforms. From fasteners to interlocks, from connector logic to communication buses, the granular choices embedded in modular design dictate how safely and efficiently a battery can be maintained throughout its lifecycle. Yet, the conversation around EV battery innovation has historically been dominated by metrics such as range, acceleration, and charging time. These are important, but they tell only part of the story. A high-performance battery that cannot be safely or economically serviced becomes a liability—one that erodes customer satisfaction, elevates total cost of ownership, and undermines the environmental promise of electrification. Service design must be treated with the same rigor and foresight as performance engineering, particularly as the market moves toward commercial fleets, shared mobility, and right-to-repair advocacy. The way forward is clear. OEMs, battery developers, and standards bodies must rethink pack design from the field technician upward. This requires embedding serviceability KPIs into design reviews, leveraging technician feedback in prototyping, and embracing automation-ready modular layouts that anticipate end-of-life realities. Smart fasteners, predictive diagnostics, and technician-safe interfaces should be standard features—not afterthoughts. In the transition to electric mobility, batteries are no longer just components; they are dynamic, data-rich, missioncritical systems. Designing them to be serviceable is not optional—it is foundational to reliability, safety, and sustainability. The next generation of EV batteries must not only perform at the frontier—they must be ready for the hands that will keep them running. References [1] Arora S, Kapoor A, Shen W. Application of robust design methodology to battery packs for electric vehicles: Identification of critical technical requirements for modular architecture. Batteries. 2018 Jun 30;4(3):30. [2] Liu Z, Tan C, Leng F. A reliability-based design concept for lithium-ion battery pack in electric vehicles. Reliability Engineering & System Safety. 2015 Feb 1;134:169-77. [3] Belingardi G, Scattina A. Battery pack and underbody: integration in the structure design for battery electric vehicles—challenges and solutions. Vehicles. 2023 Apr 23;5(2):498-514. [4] Sankaran G, Venkatesan S. Standardization of electric vehicle battery pack geometry form factors for passenger car segments in India. Journal of Power Sources. 2021 Aug 1;502:230008. [5] Adebowale OJ. Battery module balancing in commercial EVs: strategies for performance and longevity. Int J Eng Technol Res Manag. 2025 Apr;9(4):162. [6] Deng J, Bae C, Denlinger A, Miller T. Electric vehicles batteries: requirements and challenges. Joule. 2020 Mar 18;4(3):511-5. [7] Chew XQ, Tan WJ, Sakundarini N, Chin CM, Garg A, Singh S. Eco-Design of Electric Vehicle Battery Pack for Ease of Disassembly. InEnabling Industry 4.0 through Advances in Mechatronics: Selected Articles from iM3F 2021, Malaysia 2022 May 15 (pp. 71-83). Singapore: Springer Nature Singapore. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2221 [8] Boti AH, Arun Sanjey Krushna SR, Eashwar MV, Shekar H, Sidhardh CR, Swathika OG. Swappable Battery Pack System for Electric Two‐Wheelers: Design, Infrastructure, and Implementation. Resilient Community Microgrids. 2025 May 6:31-80. [9] Aiello G, Quaranta S, Certa A, Inguanta R. Optimization of urban delivery systems based on electric assisted cargo bikes with modular battery size, taking into account the service requirements and the specific operational context. Energies. 2021 Aug 1;14(15):4672. [10] Joseph Chukwunweike, Andrew Nii Anang, Adewale Abayomi Adeniran and Jude Dike. Enhancing manufacturing efficiency and quality through automation and deep learning: addressing redundancy, defects, vibration analysis, and material strength optimization Vol. 23, World Journal of Advanced Research and Reviews. GSC Online Press; 2024. Available from: https://dx.doi.org/10.30574/wjarr.2024.23.3.2800 [11] Onoda S, Emadi A. PSIM-based modeling of automotive power systems: conventional, electric, and hybrid electric vehicles. IEEE Transactions on Vehicular Technology. 2004 Mar 22;53(2):390-400. [12] Pesaran A, Roman L, Kincaide J. Electric Vehicle Lithium-Ion Battery Life Cycle Management. National Renewable Energy Laboratory (NREL), Golden, CO (United States); 2023 Feb 1. [13] Chukwunweike JN, Chikwado CE, Ibrahim A, Adewale AA Integrating deep learning, MATLAB, and advanced CAD for predictive root cause analysis in PLC systems: A multi-tool approach to enhancing industrial automation and reliability. World Journal of Advance Research and Review GSC Online Press; 2024. p. 1778–90. Available from: https://dx.doi.org/10.30574/wjarr.2024.23.2.2631 [14] Guo R, Guan W, Vallati M, Zhang W. Modular autonomous electric vehicle scheduling for customized on-demand bus services. IEEE Transactions on Intelligent Transportation Systems. 2023 May 9;24(9):10055-66. [15] Lee JK, Yeo JS, Jang MC, Yoon JM, Kang DM. Mechanical durability and electrical durability of an aluminiumlaminated lithium-ion polymer battery pack for a hybrid electric vehicle. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2010 Jun 1;224(6):765-73. [16] Adepoju Adekola George, Adepoju Daniel Adeyemi. Biomarker discovery in clinical biology enhances early disease detection, prognosis, and personalized treatment strategies. Department of Health Informatics, Indiana University Indianapolis, Indiana, USA; 2024. doi: https://doi.org/10.5281/zenodo.15244690 [17] Ejedegba Emmanuel. Innovative solutions for food security and energy transition through sustainable fertilizer production techniques. World Journal of Advanced Research and Reviews. 2024 Dec;24(3):1679–1695. Available from: https://doi.org/10.30574/wjarr.2024.24.3.3877 [18] Tan WJ, Chin CM, Garg A, Gao L. A hybrid disassembly framework for disassembly of electric vehicle batteries. International Journal of Energy Research. 2021 Apr;45(5):8073-82. [19] Chukwunweike Joseph, Salaudeen Habeeb Dolapo. Advanced Computational Methods for Optimizing Mechanical Systems in Modern Engineering Management Practices. International Journal of Research Publication and Reviews. 2025 Mar;6(3):8533-8548. Available from: https://ijrpr.com/uploads/V6ISSUE3/IJRPR40901.pdf [20] Harper G, Sommerville R, Kendrick E, Driscoll L, Slater P, Stolkin R, Walton A, Christensen P, Heidrich O, Lambert S, Abbott A. Recycling lithium-ion batteries from electric vehicles. nature. 2019 Nov;575(7781):75-86. [21] Rao GV, Bharathi MA, Kumar S, Murali B, Rao VV. Modular battery management system architecture for commercial vehicle applications. Materials Today: Proceedings. 2023 Jan 1;92:1538-43. [22] Beghi M, Braghin F, Roveda L. Enhancing disassembly practices for electric vehicle battery packs: a narrative comprehensive review. Designs. 2023 Sep 22;7(5):109. [23] Ugwueze VU, Chukwunweike JN. Continuous integration and deployment strategies for streamlined DevOps in software engineering and application delivery. Int J Comput Appl Technol Res. 2024;14(1):1–24. doi:10.7753/IJCATR1401.1001. [24] Kumar R. Lithium-Ion battery for electric transportation: Types, components, pack design, and technology. InEnergy Efficient Vehicles 2024 (pp. 156-172). CRC Press. [25] Enemosah A. Intelligent Decision Support Systems for Oil and Gas Control Rooms Using Real-Time AI Inference. International Journal of Engineering Technology Research & Management. 2021 Dec;5(12):236–244. Available from: https://doi.org/10.5281/zenodo.15363753 [26] Ramirez-Meyers K, Rawn B, Whitacre JF. A statistical assessment of the state-of-health of LiFePO4 cells harvested from a hybrid-electric vehicle battery pack. Journal of Energy Storage. 2023 Mar 1;59:106472. World Journal of Advanced Research and Reviews, 2025, 26(02), 2205-2222 2222 [27] Parkinson L, Cheung WM. Predicting the most economical option of managing electric vehicle battery at the end of its serviceable life. Cleaner Engineering and Technology. 2024 Dec 1;23:100829. [28] Adegboye O. Integrating renewable energy in battery gigafactory operations: Techno-economic analysis of netzero manufacturing in emerging markets. World J Adv Res Rev. 2023;20(02):1544–1562. doi: https://doi.org/10.30574/wjarr.2023.20.2.2170. [29] Rawat S, Choudhury S, Saini DK, Gupta YC. Advancements and Current Developments in Integrated System Architectures of Lithium-Ion Batteries for Electric Mobility. World Electric Vehicle Journal. 2024 Aug 28;15(9):394. [30] Enemosah A. Implementing DevOps Pipelines to Accelerate Software Deployment in Oil and Gas Operational Technology Environments. International Journal of Computer Applications Technology and Research. 2019;8(12):501–515. Available from: https://doi.org/10.7753/IJCATR0812.1008 [31] Blom C, Sjögren E. Design of a swappable battery pack. [32] Ejedegba Emmanuel Ochuko. Synergizing fertilizer innovation and renewable energy for improved food security and climate resilience. Global Environmental Nexus and Green Policy Initiatives. 2024 Dec;5(12):1–12. Available from: https://doi.org/10.55248/gengpi.5.1224.3554 [33] O'Connell TC, Raczkowski BC, Amrhein M, Wells JR, Tavernini MJ, Krein PT, Banner J. A modular power system architecture for military and commercial electric vehicles. SAE Technical Paper; 2010 Nov 2. [34] Warner JT. The handbook of lithium-ion battery pack design: Chemistry, components, types, and terminology. Elsevier; 2024 May 14. [35] Arvidsson J, Penndal J. Modularity in Chassis Design An investigation of modular product architecture for a chassis of an autonomous electric truck. [36] Adegboye Omotayo Abayomi. Development of a pollution index for ports. Int J Sci Res Arch. 2021;2(1):233–258. Available from: https://doi.org/10.30574/ijsra.2021.2.1.0017 [37] Enemosah A, Chukwunweike J. Next-Generation SCADA Architectures for Enhanced Field Automation and RealTime Remote Control in Oil and Gas Fields. Int J Comput Appl Technol Res. 2022;11(12):514–29. doi:10.7753/IJCATR1112.1018. [38] Chukwunweike J, Lawal OA, Arogundade JB, Alade B. Navigating ethical challenges of explainable AI in autonomous systems. International Journal of Science and Research Archive. 2024;13(1):1807–19. doi:10.30574/ijsra.2024.13.1.1872. Available from: https://doi.org/10.30574/ijsra.2024.13.1.1872. [39] Adegboye O, Olateju AP, Okolo IP. Localized battery material processing hubs: assessing industrial policy for green growth and supply chain sovereignty in the Global South. Int J Comput Appl Technol Res. 2024;13(12):38– 53. doi:10.7753/IJCATR1312.1006. [40] Adegboye Omotayo, Arowosegbe Oluwakemi Betty, Prosper Olisedeme. AI Optimized Supply Chain Mapping for Green Energy Storage Systems: Predictive Risk Modeling Under Geopolitical and Climate Shocks 2024. International Journal of Advance Research Publication and Reviews. 2024 Dec;1(4):63-86. Available from: https://ijarpr.com/uploads/V1ISSUE4/IJARPR0206.pdf [41] Ejedegba Emmanuel Ochuko. Advancing green energy transitions with eco-friendly fertilizer solutions supporting agricultural sustainability. International Research Journal of Modernization in Engineering, Technology and Science. 2024 Dec;6(12):1970. Available from: https://www.doi.org/10.56726/IRJMETS65313