Battery swapping is an intuitively appealing solution to one of electric mobility’s most persistent practical problems: the time cost of recharging. A Keke NAPEP operator whose livelihood depends on maximising fare-paying trips in an eight to twelve hour working day cannot afford eight hours off-road while a battery charges on AC current.

Battery swapping resolves this commercially by separating the vehicle from its energy storage: the operator exchanges a depleted pack for a fully charged one in minutes and returns to service. In Rwanda and Kenya, Ampersand performs approximately 140,000 monthly battery swaps for electric motorcycle taxi operators ([13]).

Spiro operates over 22,000 electric motorbikes across seven African countries, having performed more than 15 million swaps ([23]). In Nigeria, Bolt launched electric tricycles with a battery swap station in Lagos in May 2025 ([2]), while startup Swap launched a battery-as-a-service model for tricycle riders in 2024 ([8]).

The commercial enthusiasm for battery swapping in Nigeria’s Keke NAPEP market has run substantially ahead of the technical and economic evidence base for whether the model is viable specifically for the Keke NAPEP conversion market. The documented successes of Spiro and Ampersand are concentrated in two-wheeler applications—electric motorcycles with battery packs in the 1 to 2 kWh range, weighing approximately 8 to 15 kg, operating within tightly controlled networks using purpose-built vehicles with standardised battery form factors.

The Keke NAPEP tricycle requires battery packs in the 7 to 10 kWh range to sustain a full commercial day, with individual pack weights exceeding 50 kg—a fundamentally different deployment context that the existing battery swapping literature has not evaluated. This paper provides that evaluation.

This paper is a structured comparative technical and economic assessment. It argues specifically that battery swapping is not viable as the primary energy replenishment architecture for converted Keke NAPEP tricycles in Nigeria at the current stage of the country’s electrification trajectory, and that decentralised DC fast charging is the superior alternative for this specific context.

A peer-reviewed study examining the potential of EV battery swapping in developing countries, using China’s experience as a baseline for sub-Saharan Africa, found that battery swapping presents significant opportunities to augment the usability and operational efficiency of electric vehicles in developing countries, and that adaptation for sub-Saharan Africa should focus on high-use fleets like motorcycle taxis to prove economic viability before broader rollout ([22]).

The study identified robust supportive policies, targeted strategic investments, and contextually appropriate technological innovations as indispensable enabling conditions. A stakeholder study in Zambia applied Rogers’ Innovation Diffusion Model and identified compatibility with existing infrastructure and vehicle types as a core determinant of battery swapping adoption success ([21]).

The [13] Global EV Outlook [13] confirmed that Africa has seen increased investment in battery swapping technologies for two-wheelers, while noting that growth momentum is concentrated in segments where standardisation, smaller pack sizes, and controlled fleet operations create enabling conditions for the model’s success ([13]).

The literature review reveals a critical asymmetry: while the two-wheeler battery swapping evidence base is growing rapidly, three-wheeler battery swapping studies are substantially thinner and operate under conditions that differ materially from the Nigerian Keke NAPEP conversion context.

Three-wheeler battery packs are 4 to 7 times heavier and more energy-intensive than motorcycle packs. International manual handling standards establish that packs above approximately 25 kg require mechanical assistance or team handling placing a 45 to 55 kg tricycle battery pack well beyond safe single-operator manual handling thresholds ([14]). ARC Ride’s battery-as-a-service model uses 1.44 kWh packs within the safe handling envelope ([11]). No published peer-reviewed study has evaluated battery swapping specifically for the Keke NAPEP tricycle at its required energy capacity in Nigeria’s specific infrastructure and operator environment.

Research from Stellenbosch University demonstrated through a 6000 km solar-powered electric motorcycle journey from Kenya to South Africa that decentralised solar charging systems are technically feasible for electric two- and three-wheelers across sub-Saharan Africa’s diverse infrastructure environments ([5]).

A comprehensive review of EV charging infrastructure for micromobility vehicles confirmed that establishing an extensive network of low-cost, decentralised charging points is the key to alleviating range anxiety and reducing limited accessibility of electric micromobility vehicles ([6]). The Power Africa programme documented that solar-powered charging points and storage systems can support electric motorcycles and tricycles where conventional grid infrastructure is weak ([18]). These findings directly support the decentralised DC fast charging model proposed in this paper as suggestions towards decarbonisation and sustainable infrastructure delivery ([16]).

China’s battery swapping ecosystem is the model from which most developing-country battery swapping proposals draw inspiration and is built on the GB/T standard specifying connector interfaces, communication protocols, and physical dimensions for swappable battery packs ([21]). India’s battery swapping ecosystem is developing under the NITI Aayog’s draft battery swapping policy, which similarly prioritises standardisation as the foundational enabling condition ([13]).

Nigeria’s Keke NAPEP conversion market has no equivalent standardisation framework. Conversion kit suppliers entering the Nigerian market use different battery pack form factors, connector standards, BMS communication protocols, and voltage architectures making cross-operator battery interchangeability structurally impossible in the current market environment. For every EV in a swapping network, operators need 1.5 to 2 batteries available to ensure readiness, requiring enormous capital infusion and standardisation enforcement to achieve scale ([20]).

Three theoretical frameworks underpin this paper’s analysis. The Technology-Context Fit framework holds that a technology’s viability in a given deployment context is determined by the match between its structural requirements and the specific institutional, infrastructural, and operational conditions of the context ([27]). Battery swapping’s structural requirements standardisation, reliable power supply, safe manual handling weight, physical security, and fleet homogeneity are not met by Nigeria’s Keke NAPEP conversion market.

The systemic risk and centralisation framework holds that centralised infrastructure systems in which many users depend on a few critical nodes are inherently more vulnerable to failure events than distributed systems ([24]).

A battery swapping station is a single point of failure for all dependent vehicles; a failure event in Nigeria’s grid environment is near-certain annually. The Total Cost of Ownership framework evaluates all lifecycle costs rather than upfront price alone. Data from [25] in Figure 1 below highlights Nigeria’s Petrol and Electricity price trends 2000-2026.

Figure 1. Nigeria’s petrol and electricity price trends 2000-2026.

Applied to the Keke NAPEP context, it reveals a structural cost premium for battery swapping through pack duplication and station CAPEX/OPEX recovery costs ultimately borne by the operator through per-swap tariff premiums.

These frameworks are integrated in a sequential logic chain: TCF establishes whether the model can function; Systemic Risk quantifies its vulnerability; TCO establishes whether it is financially rational. A model that fails all three simultaneously is not viable regardless of its performance in other contexts.

Three specific analytical gaps motivate this study.

Firstly, no published peer-reviewed study has systematically evaluated battery swapping against the specific technical and operational realities of the Nigerian Keke NAPEP conversion market, distinguishing it from the two-wheeler contexts where the model has demonstrated viability.

Secondly, no study has provided field-measured DC fast charging time data for the LFP battery packs used in Nigerian Keke NAPEP conversions at the validated capacity and voltage architecture, directly addressing the downtime objection through experimental evidence rather than theoretical calculation.

Thirdly, no study has applied the Technology-Context Fit, Systemic Risk, and TCO frameworks simultaneously to the battery swapping versus DC fast charging comparison in the Nigerian paratransit context, nor produced a quantitative comparative cost breakdown with NPV analysis grounded in Nigerian market pricing.

This study adopts a structured comparative analytical research design in which two alternatives, battery swapping and DC fast charging are evaluated against a common, predefined set of seven criteria using a combination of quantitative engineering evidence, primary experimental field data, secondary market data, and qualitative institutional analysis.

Structured comparative analysis is a well-established methodology in technology policy research when randomised experimental designs are not feasible ([29]; [17]). The research design proceeds through four phases as described below.

Phase One identifies the seven evaluative criteria against which battery swapping is assessed. These criteria are derived from three sources: the general battery swapping literature’s identification of the structural requirements that battery swapping models must meet to function viably; the field testing programme documented in the companion study (Alade & Owotemu, Paper 1) which identified connector degradation, standardisation absence, and capital concentration as binding constraints through direct experimentation; and the engineering literature on high-current connector reliability, manual handling safety standards, and the thermal implications of repeated high-current disconnection.

The seven criteria are power infrastructure reliability, capital and operational cost structure, centralisation and systemic risk, physical security vulnerability, battery technology and chemistry constraints, mechanical and electrical reliability, and human factors and occupational safety cover the full range of dimensions that determine whether a charging model can function as a mass-market solution for the Keke NAPEP conversion context.

Phase Two documents the DC fast charging experimental programme. The following experimental parameters are stated precisely to enable independent assessment of the results presented in Table 1:

Table 1. DC Fast Charging Experimental Performance Results—96 V, 80 Ah LFP Battery Pack. All data from companion field study ([1]). Ambient conditions: Nigerian urban environment, 33˚C - 38˚C. SOC determined by BMS terminal voltage and charge termination event. Sources for validation benchmarks: [26]; [9]; [4].

Batteryundertest: one 96 V, 80 Ah lithium iron phosphate prismatic pack (7.68 kWh nominal; 6.91 kWh usable at 90% depth of discharge), with an integrated BMS providing cell-level monitoring, temperature sensing, and CC-CV charge termination. This is the validated battery architecture from the companion study.

Numberofbatterypackstested: one pack (the companion study’s single converted vehicle battery). The experimental programme tests the validated specification rather than a population of packs; manufacturing consistency across multiple packs is identified as a future research direction.

Numberofchargecycles: 12 cycles across 6 test days for optimized DC (3 - 5 kW); 8 cycles across 4 test days for experimental fast DC (8 - 10 kW); 6 cycles across 3 test days for AC baseline. Multiple-day repetition distinguishes systematic charging behaviour from day-specific ambient variation.

Chargerspecifications: Optimised DC, a 3 to 5 kW compact DC charger unit with LFP-compatible CC-CV charge profile, commercially available in the Nigerian market; experimental fast DC, an 8 to 10 kW DC fast charger unit sourced for field testing purposes. Both units deliver regulated DC output directly to the battery terminals, bypassing the onboard AC charger.

Chargingcurrent: Optimised DC delivers approximately 40 to 52 A at 96 V during the constant-current phase, corresponding to a charge rate of approximately 0.5 to 0.65 C relative to the 80 Ah capacity, consistent with the charge rate at which LFP cells maintain > 90% charging efficiency across the 20˚C to 50˚C ambient range ([9]). Experimental fast DC delivers approximately 80 to 100 A, corresponding to approximately 1.0 to 1.25 C.

Ambienttemperature: 33˚C to 38˚C across all test days, representative of Nigerian urban daytime operating conditions. This temperature range is within the LFP safe operating envelope (<60˚C cell temperature); ([26]) confirms LFP packs with passive cooling maintain 82% capacity after 1000 cycles at 35˚C, consistent with the pack’s expected performance profile.

Initialstateofcharge: 5% at the start of each charge cycle, as determined by the BMS terminal voltage reading. This represents the worst-case commercial scenario, an operator returning at the end of day with a near-depleted battery.

Chargecompletioncriterion: BMS charge termination event, the point at which the charger transitions out of the constant-voltage phase and the current falls below 0.05 C (4 A for the 80 Ah pack), indicating full charge. This criterion is used consistently across all cycles and both configurations, ensuring comparability.

Phase Three integrates the battery swapping constraint assessment with the DC fast charging experimental results and the quantitative cost comparison into a unified comparative conclusion through the three theoretical frameworks. The integration logic is presented explicitly in Section 8.1 in response to the reviewer’s question about how the seven criteria are combined into a final judgment.

This study is calibrated to the Keke NAPEP conversion market which include the diverse, independent-operator, heterogeneous-vehicle segment rather than to tightly controlled, purpose-built electric tricycle fleets such as Bolt’s Lagos deployment. The DC fast charging experimental data reflects the single validated battery architecture from the companion study; manufacturing variation across multiple packs is not captured and is identified as a future research priority.

The cost comparison in Table 2 uses central-case estimates based on verified Nigerian market pricing as of 2024-2025; costs are subject to market variation and should be reverified before investment decisions. The NPV analysis applies a 20% discount rate reflecting typical Nigerian commercial financing conditions; operators accessing concessional climate finance at lower rates would see higher NPV figures for both models but with the relative advantage of DC charging preserved.

Internal validity of the constraint assessment is protected by grounding each criterion in Nigerian-specific evidence rather than generic developing-country assumptions: the grid reliability constraint uses [15]’s verified [15] data; the connector degradation constraint uses field observation from Paper 3 under actual Nigerian operating conditions; the manual handling constraint uses the specific measured weight (45 - 55 kg) of the validated battery architecture against published safety thresholds. Internal validity of the DC fast charging experimental data is protected by the multiple-cycle, multiple-day repetition protocol that distinguishes systematic performance from day-specific variation, and by the consistent use of the BMS charge termination event as the completion criterion across all cycles and configurations ([7]).

External validity is explicitly bounded by the scope of the analysis: the Keke NAPEP conversion market comprising independent operators using heterogeneous converted vehicles. The findings do not apply directly to purpose-built electric tricycle fleets within controlled operator networks, where some standardisation constraints do not apply.

Construct validity: each of the seven criteria is operationalised to capture the specific property it is designed to measure grid reliability as the ability to maintain charged battery inventory continuously, manual handling risk as the ratio of pack weight to the safe handling threshold, connector degradation as the progressive safety risk from contact resistance increase under repeated high-current disconnection. Reliability: quantitative cost calculations are deterministic given stated assumptions, ensuring replicability; the analytical reliability of the qualitative constraint assessments is secured by triangulation across three independent evidence streams, the companion field study, published engineering literature, and verified institutional data that converge on the same constraint findings from different methodological directions ([29]).

DC Fast Charging Experimental Results

Table 1 presents the complete DC fast charging experimental results from the companion field study, including all experimental parameters requested by the reviewer. The results establish that optimised DC charging (3 - 5 kW) achieves a mean full charge time of approximately 120 minutes from 5% SOC, with low cycle-to-cycle variance (±8 minutes) across 12 measured cycles at 33˚C - 38˚C ambient.

Experimental fast DC (8 - 10 kW) achieves a mean of approximately 45 minutes (±6 minutes) across 8 cycles. These results directly and empirically address the primary commercial argument for battery swapping—the elimination of operator downtime—demonstrating that DC fast charging at power levels commercially available in the Nigerian market eliminates the 6+ hour AC charging constraint that the battery swapping literature treats as the baseline comparison.

Table 2 presents the quantitative cost comparison between battery swapping and DC fast charging for the Keke NAPEP conversion context. All figures are based on verified Nigerian market pricing as of 2024-2025 and central-case assumptions that are stated explicitly in the table.

The NPV calculations use a 5-year vehicle operational horizon and a 20% discount rate, reflecting Nigerian commercial financing conditions. The comparison demonstrates that the DC fast charging model delivers a higher NPV by ₦0.8 - ₦1.3 million per converted vehicle over five years, a shorter payback period by approximately 3 - 4 months, and a lower daily energy cost by ₦300 - ₦640 per vehicle per day.

Table 3 presents the formal seven-criteria scoring matrix for battery swapping and DC fast charging. For each criterion, the table states the score, the basis for the judgment, and—critically—whether failure on that criterion alone is individually sufficient to reject battery swapping as the primary charging architecture for this deployment context. This last column directly addresses the reviewer’s question about how the criteria are integrated into a final judgment.

Table 3. Seven-criteria scoring matrix—Battery Swapping vs DC Fast Charging for Keke NAPEP Conversion Context. The highlighted row shows the overall verdict. Yellow highlight indicates criteria where battery swapping fails sufficiently to individually reject the model. Sources: see individual criterion rows.

The criteria are not formally weighted in a multi-criteria decision matrix, and the study does not assign numerical weights. The justification for this approach is as follows: the seven criteria were not designed to be traded off against each other. They were designed to identify binding constraints, conditions that individually prevent the battery swapping model from functioning safely and sustainably in this deployment context regardless of how well it performs on other criteria.

A model that fails on grid reliability alone would still be unable to maintain charged battery inventory during Nigeria’s documented grid collapses, regardless of its performance on cost, security, or safety. A model that fails on connector degradation alone would still create progressive electrical safety risks that worsen over the vehicle’s commercial life, regardless of cost advantages. A model that fails on manual handling safety alone would still expose operators to foreseeable musculoskeletal injury risks that violate occupational health standards, regardless of operational convenience.

Table 3 makes this logic explicit in the “Individually Sufficient to Reject Swapping?” column. Five of the seven criteria are individually sufficient to reject battery swapping in this context: grid reliability, capital and operational cost structure, centralisation and systemic risk, battery technology and chemistry constraints, mechanical and electrical reliability, and human factors safety.

Physical security vulnerability (Criterion 4) is identified as a significant but not individually sufficient constraint because it is manageable with investment, it worsens the economics of battery swapping but does not make it structurally impossible in the way the other five criteria do. The overall verdict is that battery swapping FAILS on 6 of 7 criteria, with 5 individually sufficient to reject, is therefore not a weighted sum but a structural finding: the model fails on a majority of individually decisive dimensions, making the aggregate verdict unambiguous.

Applying the Technology-Context Fit framework to Table 3 confirms that battery swapping’s structural requirements are not met in the Nigerian Keke NAPEP conversion market at its current stage. The model that works for Spiro’s managed motorcycle fleet in Rwanda standardised purpose-built vehicles, 1.44 kWh pack weights of approximately 8 to 10 kg, reliable Kigali power infrastructure does not transfer to Nigeria’s conversion market operating with heterogeneous vehicles, 7.68 kWh packs weighing 45 to 55 kg, unreliable grid infrastructure, and no standardisation framework.

The Systemic Risk framework quantifies the single-point-of-failure vulnerability as a near-certain annual occurrence: with grid collapse frequency exceeding twelve times per year, the expected number of station outages attributable to grid failures alone is sufficient to cause material annual income disruption for dependent operators. The TCO framework, now grounded in the quantitative cost comparison in Table 2, confirms that battery swapping imposes a structural cost premium approximately ₦365,000 more per vehicle per year through pack duplication and station CAPEX/OPEX recovery, delivering lower NPV and longer payback than DC fast charging across the central-case parameter range.

The convergence of the experimental results in Table 1, the cost comparison in Table 2, and the criteria scoring matrix in Table 3 on a single conclusion that DC fast charging with solar-battery backup is the superior energy replenishment architecture for the Nigerian Keke NAPEP conversion market is this study’s central contribution.

The conclusion is explicitly bounded: it applies to the conversion market (heterogeneous vehicles, independent operators) rather than to purpose-built electric tricycle fleets within controlled networks, where some standardisation constraints are resolved by design.

As Table 3 acknowledges, if battery standardisation were achieved across the Nigerian conversion market through regulatory intervention under the Electric Vehicle Transition and Green Mobility Bill 2025, criteria 5 (battery technology constraints) would be resolved and a reassessment of battery swapping viability would be warranted. The study’s recommendations in Section 9 include standardisation as a policy priority precisely for this reason.