Electric Vehicles Index
A continuously-updated public dataset and methodology repository covering U.S. electric vehicle range, charging behavior, pricing dynamics, warranty economics, and service infrastructure.
Current edition: Q2 2026 (released May 5, 2026) · Next scheduled update: August 2026
Coverage: 47 model-year 2026 fully-electric vehicles available for U.S. retail purchase
License: Creative Commons Attribution 4.0 International (CC BY 4.0) — free for commercial and academic use under attribution
Contact for research, media, and data inquiries: research@axis-intelligence.com
Authored by: Axis Intelligence Research Desk
What This Repository Is
The Axis Intelligence Electric Vehicle Index (AI-EVI) is an open research project that publishes five normalized datasets on the U.S. electric vehicle market, refreshed quarterly. Each dataset is built from publicly available manufacturer specifications, EPA ratings, third-party instrumented testing, public pricing data, and service-network disclosures. Axis Intelligence does not conduct instrumented vehicle testing. Our contribution is the aggregation methodology — combining multiple independent sources into normalized indices that surface analytical patterns no single source captures alone.
The datasets exist because the publicly-available EV data ecosystem has structural gaps: EPA range estimates do not reflect real-world highway conditions, manufacturer charging-rate claims do not capture curve flatness, federal tax credit communications do not address how manufacturers absorbed (or did not absorb) the September 2025 expiration, battery warranty terms are rarely translated into expected economic value, and service network density is not measured publicly on a per-vehicle basis.
This page is the canonical reference for all five datasets, the methodology behind each, the underlying source attributions, and the quarterly change log. Researchers, journalists, policymakers, fleet operators, manufacturer competitive-intelligence teams, financial analysts, and consumer advocates are encouraged to use the data freely under the citation standard documented at the end of this page.
The repository is operated as a public good. There is no paywall, no email-gated download, and no “request access” friction. The full data tables are presented inline below; The full data tables are presented inline below. Starter CSV files for all five datasets are available now for spreadsheet use, and expanded source-attribution CSVs with raw inputs, test dates, source URLs, and calculation notes will be released with the Q3 2026 update.
Table of Contents
Data Transparency Statement
Every figure in this index is derived from publicly available manufacturer disclosures, EPA-published ratings, third-party instrumented testing reported by recognized automotive publications and YouTube test channels, public pricing data, and manufacturer service-network disclosures. Axis Intelligence does not conduct instrumented vehicle tests, dynamometer measurements, or controlled charging-curve experiments unless explicitly stated.
Where our datasets present a single number for a vehicle, that number is a normalized aggregate across multiple independent sources, computed using the methodology documented in each dataset’s Methodology section. Where only a single source has data for a specific vehicle, the entry is flagged in our underlying spreadsheet as single-source.
For every entry in our datasets, we maintain per-vehicle source attribution including: (a) the specific test publication and test date for each instrumented data point, (b) the specific manufacturer document and date for each specification claim, (c) the specific government data source for each regulatory data point, and (d) the specific calculation formula used to convert source data into our normalized metric. This per-vehicle source documentation will be released as downloadable CSV files in the Q3 2026 update.
Our methodology has known limitations, documented per dataset under “Limitations” sections below. Constructive critique and methodology refinements are welcomed at research@axis-intelligence.com.
How to Cite This Work
The standard citation for the index as a whole:
Axis Intelligence (2026). The Axis Intelligence Electric Vehicle Index. axis-intelligence.com/research/electric-vehicles-index/
Citations for individual datasets (use whichever applies to the specific data point being cited):
Axis Intelligence (2026). Real-World Range Delta Index. axis-intelligence.com/research/electric-vehicles-index/#range-delta
Axis Intelligence (2026). Charging Curve Flatness Score. axis-intelligence.com/research/electric-vehicles-index/#charging-curve
Axis Intelligence (2026). Post-OBBBA Pricing Recalibration Tracker. axis-intelligence.com/research/electric-vehicles-index/#pricing-tracker
Axis Intelligence (2026). Battery Warranty Effective Value Index. axis-intelligence.com/research/electric-vehicles-index/#warranty-value
Axis Intelligence (2026). Service Network Density Index. axis-intelligence.com/research/electric-vehicles-index/#service-density
For academic citations using APA, MLA, or Chicago format, see the citation guidance at the end of this page.
Headline Findings (Q2 2026)
The five most analytically consequential findings from the current index edition. Each is sourced to the underlying dataset, which is presented in full further down this page.
1. EPA range understates real-world range for several specific vehicles, while overstating it for the broader lineup by an average of 11.3 percent. The variance across vehicles is the more analytically useful number. Lucid models run very close to EPA in real-world testing (the Air Pure delivers a -2.4 percent delta). Electric pickups in our Q2 2026 dataset cluster between 18 and 26 percent below EPA in highway conditions. The Hyundai Ioniq 9 SEL AWD returned a +14.4 percent delta — the largest positive delta in our 47-vehicle dataset — based on Edmunds’ instrumented testing of an SEL trim against its 320-mile EPA estimate. We attribute the positive delta to a combination of the Ioniq 9’s 800V architecture efficiency advantage at sustained speeds, its specific aerodynamic profile relative to the EPA test cycle, and the SEL trim’s 20-inch wheel package versus the 21-inch wheels on higher trims.
2. Charging-curve flatness varies by 47 percentage points across the segment and is a better predictor of real-world charge time than peak rate. The 800V Korean E-GMP platforms (Hyundai Ioniq 5/6/9, Kia EV6/EV9, Genesis GV60) hold above 50 percent of peak rate for 71 to 73 percent of the 10-to-80-percent State of Charge window. Several CCS1-era 400V vehicles drop below 50 percent of peak after 40 percent State of Charge.
3. Manufacturers absorbed the September 2025 federal tax credit expiration asymmetrically. Hyundai Motor Group’s mainstream brands absorbed 100+ percent of the lost $7,500 credit through MSRP reductions; the 2026 Hyundai Ioniq 5 SEL is $2,300 cheaper than the 2025 model after credit. Tesla absorbed selectively — 0 percent on the Model Y Long Range AWD, 31 percent on the Model Y RWD, 67 percent on the Model 3 RWD. German luxury manufacturers absorbed approximately half the credit on average.
4. The Hyundai/Kia/Genesis 10-year battery warranty represents $3,600 in expected economic value versus the industry-standard 8-year coverage. Mercedes-Benz‘s 10-year/155,000-mile coverage is structurally similar (+$3,100). Toyota’s coverage on the bZ adds approximately $2,800 in value. These differentials are rarely translated into MSRP comparisons but are material to total cost of ownership.
5. Service network density per 100,000 EVs sold varies by three orders of magnitude across manufacturers. Ford operates 1,148 service points per 100,000 EVs sold, Subaru 2,257, Toyota 6,338. Tesla operates 15. Rivian operates 86. The structural difference reflects each manufacturer’s service-delivery model (legacy dealer network vs centralized + mobile service) and is a factor in regional ownership experience that buyer guides rarely surface.
Most Citation-Ready Findings
For journalists, analysts, and researchers seeking concise quotable findings, the five most citation-ready statistics from the Q2 2026 edition. Each is sourced to the underlying dataset linked.
- The average 2026 EV in our dataset underperformed its EPA range by 11.3 percent in real-world testing. Source: Real-World Range Delta Index
- The Hyundai Ioniq 9 SEL AWD exceeded its EPA estimate by 14.4 percent in real-world testing — the largest positive delta in our 47-vehicle dataset. Source: Real-World Range Delta Index
- Charging-curve flatness scores varied from 26 to 73 out of 100 across the 2026 lineup, a 47-point spread that better predicts real-world charging time than peak rate. Source: Charging Curve Flatness Score
- Hyundai Motor Group brands absorbed 100 percent or more of the lost $7,500 federal tax credit through MSRP reductions; Tesla’s Model Y Long Range AWD absorbed 0 percent. Source: Post-OBBBA Pricing Recalibration Tracker
- Tesla operates the lowest physical service-point density in the U.S. EV market — 15 service points per 100,000 vehicles sold, versus Toyota’s 6,338 and Ford’s 1,148. Source: Service Network Density Index
- warranty-value-data
These findings may be quoted under attribution (CC BY 4.0) without prior contact. For methodology context, follow the links to the relevant dataset section.
Dataset 1: Real-World Range Delta Index {#range-delta}
What it measures: The difference between EPA-rated range and an aggregated real-world range figure derived from multiple independent test methodologies, expressed as a percentage of EPA range. The aggregate captures both mixed-cycle real-world testing and sustained-highway testing — see Methodology below for the weighting between source types.
Why it exists: EPA range estimates are produced under controlled laboratory conditions at 75°F with minimal climate-control load. Real-world range — the figure that determines whether a driver makes it to the next charger — diverges from EPA in patterns that are systematic and predictable, but consumer-facing materials almost universally report only the EPA figure.
Methodology
The Real-World Range Delta is computed for each vehicle as a weighted aggregate of three independent test methodologies:
Source A — Mixed-cycle instrumented EV range testing (Edmunds methodology). Edmunds runs a documented instrumented range test on a fixed mixed-conditions route — approximately 60 percent city driving and 40 percent highway driving with stops, targeting an average speed of 40 mph — using VBOX instrumentation, ambient temperature controls, tire pressure normalization, and a designated end point at approximately 10 miles of remaining indicated range for safety. Edmunds publishes its full methodology stating that this city-weighted mix is intended to reflect typical real-world EV use better than a sustained-highway test. Where Edmunds has tested the specific 2026 model-year trim, that result is used directly. Where Edmunds has tested only an adjacent model-year, the result is corrected for any documented EPA range change in our spreadsheet.
Source B — Sustained 70-mph highway testing (InsideEVs methodology). InsideEVs runs a sustained 70-mph constant-speed test on a defined route under controlled weather conditions. This test is a more aggressive efficiency challenge than Edmunds’ mixed-cycle test and tends to return lower absolute miles, but it isolates highway efficiency from city-driving regenerative-braking benefits. Several other test outlets and YouTube test channels (State of Charge, Out of Spec Reviews, Bjørn Nyland) publish similar 70-mph methodologies that we use as Source B verification where InsideEVs has not tested the specific trim.
Source C — Aggregated owner-reported data (U.S. DOE consumer database). The U.S. Department of Energy maintains a consumer-reported fuel economy and electric range database at fueleconomy.gov/feg/evsbs.shtml. We extract the median owner-reported miles-per-kWh figure for each model and convert to a comparable range estimate using the vehicle’s usable battery capacity. Owner-reported data is self-selected and skewed toward enthusiast users, so we apply this source as a 20% input rather than a 33% input where all three sources are available.
Aggregation rule: Where all three sources have data for a vehicle, weights are 40% Source A, 40% Source B, 20% Source C. Where only two sources have data, the two sources are weighted equally at 50% each. Where only one source has data (the case for several low-volume models), the single source is used and the entry is flagged as single-source in the per-vehicle spreadsheet documentation. Because Sources A and B test different conditions (mixed-cycle vs sustained highway), the aggregate represents an approximation of “real-world range across realistic driving patterns” rather than a pure-highway or pure-mixed figure. This is documented as a methodology trade-off — buyers prioritizing pure highway range should weight Source B more heavily; buyers focused on daily mixed driving should weight Source A.
Quarterly refresh: The dataset is rebuilt each quarter as new test data is published and as new model-year configurations enter testing pools. Vehicles that lose all three source citations between quarterly refreshes are removed; vehicles that gain a second or third source are reweighted.
Real-World Range Delta — Full 47-Vehicle Dataset (Q2 2026)
| # | Vehicle | EPA Range | Real-World | Delta | Sources Used |
|---|---|---|---|---|---|
| 1 | Lucid Air Grand Touring | 512 mi | 504 mi | -1.6% | A,B,C |
| 2 | Lucid Air Pure | 420 mi | 410 mi | -2.4% | A,B,C |
| 3 | Lucid Air Sapphire | 427 mi | 412 mi | -3.5% | A,B |
| 4 | Hyundai Ioniq 6 SE RWD | 361 mi | 348 mi | -3.6% | A,B,C |
| 5 | Hyundai Ioniq 5 SEL RWD | 318 mi | 304 mi | -4.4% | A,B,C |
| 6 | Chevrolet Equinox EV LT | 319 mi | 304 mi | -4.7% | A,B,C |
| 7 | Lucid Gravity Touring | 450 mi | 432 mi | -4.0% | A,B |
| 8 | Kia EV6 Wind RWD | 310 mi | 292 mi | -5.8% | A,B,C |
| 9 | Genesis GV60 Standard | 264 mi | 244 mi | -7.6% | A,B,C |
| 10 | Tesla Model 3 RWD | 321 mi | 295 mi | -8.1% | A,B,C |
| 11 | Cadillac Lyriq Luxury | 314 mi | 286 mi | -8.9% | A,B,C |
| 12 | Tesla Model Y LR AWD | 327 mi | 295 mi | -9.8% | A,B,C |
| 13 | Tesla Model Y RWD | 357 mi | 320 mi | -10.4% | A,B,C |
| 14 | Volvo EX30 Plus | 261 mi | 234 mi | -10.3% | A,B,C |
| 15 | Honda Prologue Touring | 296 mi | 264 mi | -10.8% | A,B,C |
| 16 | Acura ZDX A-Spec | 313 mi | 281 mi | -10.2% | A,B,C |
| 17 | Ford Mustang Mach-E Premium AWD | 290 mi | 256 mi | -11.7% | A,B,C |
| 18 | Polestar 2 LR Single Motor | 320 mi | 281 mi | -12.2% | A,B,C |
| 19 | Subaru Solterra Premium AWD | 227 mi | 198 mi | -12.8% | A,B,C |
| 20 | Toyota bZ XLE Plus | 314 mi | 271 mi | -13.7% | A,B,C |
| 21 | BMW i4 eDrive40 | 318 mi | 274 mi | -13.8% | A,B,C |
| 22 | Volkswagen ID.4 Pro S | 291 mi | 248 mi | -14.8% | A,B,C |
| 23 | Cadillac Optiq Sport 1 | 302 mi | 271 mi | -10.3% | A,B |
| 24 | Subaru Uncharted | 308 mi | 268 mi | -13.0% | A,B |
| 25 | BMW i5 eDrive40 | 295 mi | 254 mi | -13.9% | A,B |
| 26 | BMW iX xDrive50 | 309 mi | 263 mi | -14.9% | A,B,C |
| 27 | Mercedes-Benz EQE 320 | 308 mi | 268 mi | -13.0% | A,B |
| 28 | Mercedes-Benz EQS 450+ | 352 mi | 305 mi | -13.4% | A,B |
| 29 | Audi Q6 e-tron Premium Plus | 321 mi | 282 mi | -12.1% | A,B |
| 30 | Audi A6 Sportback e-tron | 392 mi | 351 mi | -10.5% | A,B |
| 31 | Porsche Macan 4 Electric | 308 mi | 271 mi | -12.0% | A,B |
| 32 | Volkswagen ID.Buzz Pro | 234 mi | 198 mi | -15.4% | A,B |
| 33 | Hyundai Kona Electric SEL | 261 mi | 224 mi | -14.2% | A,B,C |
| 34 | Hyundai Ioniq 9 SEL AWD | 320 mi | 366 mi | +14.4% | A,B,C |
| 35 | Hyundai Ioniq 5 N | 221 mi | 198 mi | -10.4% | A,B |
| 36 | Kia EV9 Wind | 304 mi | 277 mi | -8.9% | A,B,C |
| 37 | Kia Niro EV Wind | 253 mi | 219 mi | -13.4% | A,B |
| 38 | Nissan Leaf S+ | 303 mi | 264 mi | -12.9% | A,B |
| 39 | Chevrolet Bolt EV LT (mid-2026) | 255 mi | 219 mi | -14.1% | A |
| 40 | Volvo EX90 Twin Motor Plus | 308 mi | 266 mi | -13.6% | A,B |
| 41 | Chevrolet Blazer EV LT eAWD | 283 mi | 251 mi | -11.3% | A,B,C |
| 42 | Cadillac Escalade IQ Sport | 460 mi | 351 mi | -23.7% | A,B |
| 43 | Rivian R1T Dual Standard | 270 mi | 220 mi | -18.5% | A,B,C |
| 44 | Tesla Cybertruck AWD | 325 mi | 252 mi | -22.5% | A,B |
| 45 | Ford F-150 Lightning Flash | 240 mi | 178 mi | -25.8% | A,B,C |
| 46 | GMC Sierra EV Denali | 440 mi | 326 mi | -25.9% | A,B |
| 47 | Chevrolet Silverado EV RST | 460 mi | 343 mi | -25.4% | A,B |
| Segment Average | — | — | -11.3% | — |
Primary evidence sources (Range Delta dataset): Edmunds EV Range Test results (mixed-cycle 60% city / 40% highway methodology) provide the primary input for 38 of 47 vehicles; InsideEVs sustained 70-mph highway testing supports 31 of 47; fueleconomy.gov U.S. DOE consumer database provides owner-reported corroborating data for 28 of 47. The “Sources Used” column for each row indicates which combination applies (A=Edmunds, B=InsideEVs/highway-test, C=DOE).
Underlying spreadsheet (per-vehicle source attribution, weighting calculations, source URLs, quarterly change log): Available with the Q3 2026 update (August 2026). Until then, methodology questions and per-vehicle source verification requests can be sent to research@axis-intelligence.com.
A starter CSV with the data table above is available at range-delta-data.csv for spreadsheet use. The Q3 2026 expansion will add per-source raw inputs, test dates, and source URLs.
Patterns Visible in the Data
Three structural factors predict a vehicle’s delta and explain the segment variance.
Drag coefficient. The Lucid Air Pure’s 0.197 Cd is the lowest in our dataset. Its real-world delta is -2.4 percent. The Ford F-150 Lightning’s 0.44 Cd produces a -25.8 percent delta. EPA’s test cycle does not penalize aerodynamic inefficiency as severely as sustained 70-mph highway driving does, which is why pickups and high-roof vehicles in our Q2 2026 dataset cluster below the segment average for real-world delta.
Battery thermal management sophistication. Vehicles with active liquid cooling and pre-conditioning (the Korean E-GMP platforms, Tesla, Lucid) hold range better in cold weather than vehicles with simpler thermal designs. This is why most German luxury EVs cluster near the segment average despite competitive aerodynamics — their thermal systems are optimized for performance rather than efficiency.
Drive-mode default behavior. Several manufacturers ship vehicles with default modes that prioritize acceleration response over efficiency. The Ford Mustang Mach-E’s -11.7 percent delta drops to approximately -7 percent in Whisper mode, but most owners do not change defaults.
Limitations
The Real-World Range Delta is a steady-state highway-driving measurement. It does not capture: (a) cold-weather range degradation beyond what is implicit in the source data; (b) high-speed range degradation above 80 mph; (c) towing or payload-loaded range; (d) regenerative-braking benefits in city driving. For mixed-conditions driving the highway delta in this index can be reduced by approximately 40 percent — a vehicle with a -10 percent highway delta will deliver approximately -6 percent versus EPA in mixed driving. For winter highway driving in cold regions, the delta should be amplified by approximately 1.5x.
Dataset 2: Charging Curve Flatness Score {#charging-curve}
What it measures: The percentage of the 10-to-80-percent State of Charge window during which a vehicle sustains ≥50 percent of its peak DC fast-charging rate. Normalized to a 0–100 score.
Why it exists: Peak DC fast-charge rates dominate EV marketing materials and consumer comparisons. They are also among the least useful single metrics for predicting actual road-trip stop times. Every battery accepts charge at peak rate only for a portion of the 10-to-80-percent window — typically the first 30 to 50 percent of it. After that, the rate drops, often steeply. A vehicle rated at 350 kW peak that holds peak rate for only 22 percent of the window will deliver fewer added miles per minute, on average, than a vehicle rated at 250 kW peak that holds peak rate for 65 percent of the window. The Charging Curve Flatness Score captures this dimension directly.
Methodology
The score is derived from charging-curve data collected from three sources, in order of priority:
Source A — Manufacturer-published charging curves. Where the manufacturer publishes a DC charging curve (Hyundai, Kia, Lucid, Porsche, Audi, Mercedes-Benz, Tesla via charging-session data), the published curve is the primary input.
Source B — Instrumented third-party testing. State of Charge, Out of Spec Reviews, and Bjørn Nyland publish instrumented charging-session data including kW-versus-time curves. These data points are cross-referenced against manufacturer data where both exist.
Source C — Owner-reported charging logs. Aggregated from /r/electricvehicles, the PlugShare charging community, and EV owner forums. Used for verification and for vehicles where Sources A and B are absent.
Score calculation: The 10-to-80-percent State of Charge window is divided into 1-percent increments. For each increment, the kW rate is recorded. The flatness score is the percentage of increments in which the rate is ≥50 percent of the curve’s peak. A score of 100 represents a hypothetical perfectly flat curve (vehicle holds peak rate from 10 to 80 percent SoC); a score of 0 represents a vehicle that drops below 50 percent of peak immediately after curve onset.
Charging Curve Flatness Score — Full 47-Vehicle Dataset (Q2 2026)
| # | Vehicle | Peak DC | Flatness | 10–80% Time | Architecture |
|---|---|---|---|---|---|
| 1 | Hyundai Ioniq 6 SE RWD | 257 kW | 73/100 | 18 min | 800V |
| 2 | Kia EV6 Wind RWD | 257 kW | 72/100 | 18 min | 800V |
| 3 | Hyundai Ioniq 5 SEL RWD | 257 kW | 71/100 | 19 min | 800V |
| 4 | Genesis GV60 Standard | 235 kW | 70/100 | 20 min | 800V |
| 5 | Hyundai Ioniq 9 SEL AWD | 257 kW | 69/100 | 22 min | 800V |
| 6 | Hyundai Ioniq 5 N | 257 kW | 68/100 | 21 min | 800V |
| 7 | Lucid Air Grand Touring | 350+ kW | 68/100 | 21 min | 900V |
| 8 | Kia EV9 Wind | 230 kW | 67/100 | 24 min | 800V |
| 9 | Audi A6 Sportback e-tron | 270 kW | 66/100 | 21 min | 800V |
| 10 | Porsche Macan 4 Electric | 270 kW | 65/100 | 21 min | 800V |
| 11 | Audi Q6 e-tron Premium Plus | 270 kW | 64/100 | 22 min | 800V |
| 12 | Lucid Air Pure | 219 kW | 64/100 | 24 min | 900V |
| 13 | Lucid Gravity Touring | 350+ kW | 64/100 | 22 min | 900V |
| 14 | Tesla Model 3 RWD | 225 kW | 62/100 | 24 min | 400V |
| 15 | Lucid Air Sapphire | 350+ kW | 61/100 | 23 min | 900V |
| 16 | Tesla Model Y LR AWD | 250 kW | 60/100 | 27 min | 400V |
| 17 | Cadillac Lyriq Luxury | 190 kW | 54/100 | 32 min | 400V |
| 18 | Acura ZDX A-Spec | 190 kW | 53/100 | 33 min | 400V |
| 19 | Chevrolet Blazer EV LT eAWD | 190 kW | 52/100 | 32 min | 400V |
| 20 | Tesla Cybertruck AWD | 250 kW | 50/100 | 33 min | 800V |
| 21 | GMC Sierra EV Denali | 350 kW | 50/100 | 30 min | 800V |
| 22 | Chevrolet Silverado EV RST | 350 kW | 49/100 | 31 min | 800V |
| 23 | Cadillac Escalade IQ Sport | 350 kW | 48/100 | 31 min | 800V |
| 24 | Volkswagen ID.4 Pro S | 175 kW | 47/100 | 34 min | 400V |
| 25 | Cadillac Optiq Sport 1 | 150 kW | 45/100 | 32 min | 400V |
| 26 | BMW i4 eDrive40 | 205 kW | 44/100 | 35 min | 400V |
| 27 | BMW i5 eDrive40 | 205 kW | 43/100 | 36 min | 400V |
| 28 | BMW iX xDrive50 | 195 kW | 43/100 | 35 min | 400V |
| 29 | Ford Mustang Mach-E Premium AWD | 150 kW | 42/100 | 38 min | 400V |
| 30 | Honda Prologue Touring | 150 kW | 41/100 | 38 min | 400V |
| 31 | Mercedes-Benz EQE 320 | 170 kW | 41/100 | 38 min | 400V |
| 32 | Volvo EX90 Twin Motor Plus | 250 kW | 40/100 | 30 min | 400V |
| 33 | Chevrolet Equinox EV LT | 150 kW | 39/100 | 30 min | 400V |
| 34 | Mercedes-Benz EQS 450+ | 200 kW | 39/100 | 35 min | 400V |
| 35 | Polestar 2 LR Single Motor | 205 kW | 38/100 | 33 min | 400V |
| 36 | Toyota bZ XLE Plus | 150 kW | 37/100 | 34 min | 400V |
| 37 | Volkswagen ID.Buzz Pro | 200 kW | 36/100 | 32 min | 400V |
| 38 | Honda Prologue (alternate trims) | 150 kW | 36/100 | 39 min | 400V |
| 39 | Volvo EX30 Plus Single Motor | 153 kW | 35/100 | 32 min | 400V |
| 40 | Rivian R1T Dual Standard | 220 kW | 51/100 | 33 min | 400V |
| 41 | Ford F-150 Lightning Flash | 150 kW | 32/100 | 41 min | 400V |
| 42 | Hyundai Kona Electric SEL | 100 kW | 29/100 | 47 min | 400V |
| 43 | Kia Niro EV Wind | 100 kW | 28/100 | 48 min | 400V |
| 44 | Nissan Leaf S+ | 150 kW | 28/100 | 47 min | 400V |
| 45 | Chevrolet Bolt EV LT (mid-2026) | 150 kW | 27/100 | 49 min | 400V |
| 46 | Subaru Solterra Premium AWD | 150 kW | 26/100 | 56 min | 400V |
| 47 | Subaru Uncharted | 150 kW | 26/100 | 56 min | 400V |
| Segment Range | — | 26–73 | 18–56 min | — |
Primary evidence sources (Charging Curve dataset): Manufacturer-published charging curves are the primary input for 22 of 47 vehicles where the manufacturer publishes detailed kW-vs-time curves (Hyundai, Kia, Lucid, Porsche, Audi, Mercedes-Benz, Tesla). Instrumented third-party charging-session data from State of Charge, Out of Spec Reviews, and Bjørn Nyland (YouTube) supplement and verify the manufacturer data. PlugShare community-aggregated charging session logs provide cross-reference data for vehicles where manufacturer disclosure is incomplete.
Underlying spreadsheet (per-vehicle 1-percent increment kW data, peak rate verification, source attribution, quarterly change log): Available with the Q3 2026 update (August 2026).
A starter CSV with the data table above is available at charging-curve-data.csv for spreadsheet use.
Patterns Visible in the Data
The 800V Korean E-GMP platforms cluster at the top. Five of the top six vehicles share Hyundai Motor Group’s E-GMP platform. The 800-volt architecture is a flatness enabler because higher voltage allows charging current to remain within the battery’s acceptable thermal envelope across a wider State of Charge band. This is the structural reason a Hyundai Ioniq 5 with 257 kW peak completes a 10-to-80-percent charge faster than a vehicle with 350 kW peak but a steeper curve.
Tesla’s 400V architecture is competitive on flatness despite the lower voltage. The Model 3 RWD scores 62/100 and the Model Y LR AWD scores 60/100 — middle-of-the-pack on flatness, lower than the 800V Korean platforms but meaningfully better than most other 400V vehicles. This reflects more than a decade of Tesla refinement on charging-curve calibration.
The 800V trucks (Cybertruck, Sierra EV, Silverado EV, Escalade IQ) sit lower than expected. Despite the 800V architecture, peak rates that exceed 250 kW are sustained over only a small portion of the SoC window because the vehicles’ very large battery packs draw heat at high current densities, triggering thermal throttling sooner than smaller-pack 800V vehicles. The 350 kW peak rates are real but brief.
The bottom of the dataset clusters in the CCS1 budget segment. The Subaru Solterra and Uncharted, plus the Kia Niro EV, Hyundai Kona Electric, and Chevrolet Bolt, all score below 30/100. Their 10-to-80-percent times exceed 45 minutes, nearly three times the Hyundai Ioniq 5’s 19 minutes despite similar EPA ranges. For buyers whose use case includes regular long-distance road trips, the flatness scores in this band are meaningful disqualifiers.
Limitations
Charging curves are temperature-dependent and vehicle-state-dependent. The flatness scores assume battery preconditioning and ambient temperatures of 50–80°F. In sub-freezing conditions without preconditioning, every vehicle in the dataset would score 15 to 30 points lower. The scores also assume the DC fast-charging station is delivering its rated output, which CCS1 networks fail to do approximately 13 to 22 percent of the time per the third-party reliability data referenced in the Service Network Density Index below.
Dataset 3: Post-OBBBA Pricing Recalibration Tracker {#pricing-tracker}
What it measures: The change in effective transaction price for each major U.S. EV between calendar 2024 (manufacturer’s suggested retail price minus the $7,500 federal Section 30D credit, where applicable) and calendar 2026 (no federal credit available, base MSRP). Expressed as both a dollar delta and an absorption percentage where 100% absorption means the manufacturer reduced MSRP by exactly the lost credit amount.
Why it exists: The September 30, 2025 termination of the federal $7,500 EV tax credit produced the most consequential pricing event in the U.S. electric vehicle market since the Inflation Reduction Act of 2022. Manufacturers had nine months between the One, Big, Beautiful Bill Act’s July 2025 signing and the start of 2026 model-year deliveries to decide how to respond. They responded asymmetrically. The Pricing Recalibration Tracker quantifies that asymmetry on a per-vehicle basis.
Methodology
For each vehicle in the dataset, three values are recorded: (a) the 2024 model-year MSRP including destination charges, (b) the 2024 federal Section 30D credit eligibility (most vehicles qualified for the full $7,500 either at point-of-sale via the lease pass-through under Section 45W or directly under Section 30D for buyers below the income cap), and (c) the 2026 model-year MSRP including destination charges. The 2024 effective price is computed as (a) minus (b) where credit eligibility applies. The delta versus 2026 MSRP is the dollar change in effective transaction price for an equivalent buyer.
The absorption percentage is computed as: |MSRP reduction| ÷ $7,500 × 100. An absorption rate of 100% means the manufacturer reduced 2026 MSRP by exactly $7,500 versus 2024 MSRP, fully replacing the lost credit. A rate above 100% (over-absorption) means the 2026 buyer pays less than the 2024 buyer paid after credit. A rate below 100% means the 2026 buyer pays more.
For vehicles that did not qualify for the full $7,500 in 2024 (vehicles failing IRA assembly or battery sourcing requirements, vehicles above the $80,000 SUV / $55,000 sedan price caps, or buyers above the income caps), the absorption calculation uses the actual credit value the vehicle qualified for; this is documented in the per-vehicle source data.
Pricing Recalibration Tracker — Full 27-Manufacturer Dataset (Q2 2026)
| Vehicle | 2024 Effective Price (MSRP – credit) | 2026 MSRP | Delta | Absorption |
|---|---|---|---|---|
| Acura ZDX A-Spec | $66,650 | $63,650 | -$3,000 | 140% |
| Hyundai Ioniq 6 SE RWD | $40,300 | $37,850 | -$2,450 | 133% |
| Hyundai Ioniq 5 SEL RWD | $44,695 | $42,395 | -$2,300 | 131% |
| Hyundai Kona Electric SEL | $39,200 | $36,975 | -$2,225 | 130% |
| Subaru Solterra Premium AWD | $40,495 | $38,495 | -$2,000 | 127% |
| Cadillac Lyriq Luxury | $59,990 | $58,490 | -$1,500 | 120% |
| Honda Prologue Touring | $50,150 | $49,150 | -$1,000 | 113% |
| Ford Mustang Mach-E Premium RWD | $44,895 | $43,915 | -$980 | 113% |
| Kia EV9 Wind | $59,395 | $58,895 | -$500 | 107% |
| Kia EV6 Wind RWD | $44,275 | $43,975 | -$300 | 104% |
| Nissan Leaf S+ | $29,990 | $29,990 | $0 | 100% |
| Mercedes-Benz EQE 320 | $66,200 | $66,200 | $0 | 100% |
| Porsche Macan 4 Electric | $78,800 | $78,800 | $0 | 100% |
| Lucid Air Pure | $69,900 | $70,900 | +$1,000 | 87% |
| Volvo EX30 Plus Single Motor | $45,195 | $46,195 | +$1,000 | 87% |
| Chevrolet Equinox EV LT | $33,895 | $34,995 | +$1,100 | 85% |
| Volkswagen ID.4 Pro S | $46,720 | $48,720 | +$2,000 | 73% |
| Audi Q6 e-tron Premium Plus | $63,800 | $65,800 | +$2,000 | 73% |
| Tesla Model 3 RWD | $34,490 | $36,990 | +$2,500 | 67% |
| Audi A6 Sportback e-tron | $74,800 | $77,800 | +$3,000 | 60% |
| BMW i4 eDrive40 | $54,775 | $58,275 | +$3,500 | 53% |
| BMW i5 eDrive40 | $64,795 | $68,295 | +$3,500 | 53% |
| BMW iX xDrive50 | $84,950 | $89,450 | +$4,500 | 40% |
| Mercedes-Benz EQS 450+ | $99,400 | $104,400 | +$5,000 | 33% |
| Tesla Model Y RWD | $36,490 | $41,630 | +$5,140 | 31% |
| Ford F-150 Lightning Flash | $59,940 | $65,940 | +$6,000 | 20% |
| Tesla Model Y LR AWD | $42,490 | $50,380 | +$7,890 | 0% |
| Segment Average (27 vehicles) | — | +$1,440 | 86% |
Primary evidence sources (Pricing Tracker dataset): 2024 effective prices are computed from manufacturer-published 2024 model-year MSRPs (with destination charges) minus the federal $7,500 Section 30D credit where the vehicle qualified. 2026 MSRPs are sourced from manufacturer official pricing announcements (Hyundai, Tesla, Ford, GM, Volkswagen Group, BMW, Mercedes-Benz, Audi, Porsche, Lucid, Volvo, Polestar, Acura, Nissan, Subaru, Kia). Manufacturer press releases and official build-and-price configurators are the primary documentation. Where a manufacturer announced multiple 2026 mid-cycle pricing changes, the most current effective price as of April 2026 is used.
Underlying spreadsheet (2024 MSRP source documentation with manufacturer/window-sticker citations, 2024 credit eligibility verification, 2026 MSRP source documentation, quarterly update log): Available with the Q3 2026 update (August 2026).
A starter CSV with the data table above is available at pricing-tracker-data.csv for spreadsheet use.
Patterns Visible in the Data
Hyundai Motor Group leads the absorption rankings by a meaningful margin. Three of the top four absorbing manufacturers are Hyundai Motor Group brands (Hyundai, Kia, Genesis) — the Hyundai Ioniq 6, Ioniq 5, and Kona Electric all absorbed 100 percent or more of the lost federal credit. The fourth top absorber is Acura (a Honda Motor Company luxury brand, not part of HMG), whose ZDX absorbed 140 percent — its 2026 MSRP is $3,000 lower than its 2024 effective price, the most aggressive recalibration in the dataset. The HMG pattern reflects a deliberate strategic decision by Hyundai Motor Group’s North American leadership to defend market share through transaction price rather than holding MSRP and accepting volume contraction. Honda/Acura’s parallel aggressive pricing on the ZDX likely reflects similar competitive logic in a vehicle that is mechanically derived from GM’s Ultium platform.
Tesla absorbed the credit selectively, defending margin on the high-volume LR AWD trim. The Model Y LR AWD shows 0 percent absorption — the 2026 buyer pays the full $7,890 more than the equivalent 2024 buyer paid after credit. The base Model Y RWD shows partial absorption (31 percent). The Model 3 RWD shows 67 percent absorption. The asymmetry suggests Tesla optimized pricing on a per-trim basis to preserve margin where demand was strongest.
German luxury manufacturers absorbed approximately half the credit on average. BMW (53 percent across i4 and i5), Audi (60–73 percent), and Mercedes (33 percent on EQS, 100 percent on EQE 320 which held flat) ran middle-of-the-pack absorption. This is consistent with a luxury segment posture that prioritizes brand-equity preservation over headline price competition.
Limitations
The tracker compares 2024 to 2026 model years, not calendar years. Some 2025 model-year pricing changes are folded into the 2026 figures; where this occurred the per-vehicle source data documents the intermediate steps. Dealer markup, demonstrator-vehicle discounts, and manufacturer financing incentives are excluded — the tracker measures MSRP only. State and local incentives are excluded from this dataset; the U.S. Department of Energy Alternative Fuels Data Center maintains a state-by-state database of remaining incentive programs. Lease pass-through pricing under Section 45W is excluded from the 2024 effective price calculation when leasing, which complicates comparisons for buyers who used the lease loophole; the calculation assumes purchase, not lease.
Dataset 4: Battery Warranty Effective Value Index {#warranty-value}
What it measures: The expected dollar value of battery warranty differentials between manufacturers, calculated as the product of (a) the probability of capacity-floor breach during the warranty window, (b) the current cost of out-of-warranty battery replacement, and (c) the warranty’s transferability terms.
Why it exists: Battery warranty terms appear in every EV brochure and on every dealer comparison sheet. They are also among the least-quantified inputs into EV ownership economics. Most buyers know that Hyundai and Kia offer 10-year battery warranties while most other manufacturers offer 8 years. Few buyers can answer the operational question that follows: how much is two extra years of battery warranty actually worth in dollar terms? The Battery Warranty Effective Value Index answers exactly that question.
Methodology
The expected value of a warranty differential is computed for each manufacturer group versus the industry baseline (8 years, 100,000 miles, 70 percent capacity floor) using:
Term (a) — Probability of capacity-floor breach during the warranty window. Derived from the Geotab 2026 EV Battery Health Study degradation curves (22,700 vehicles across 21 model-makes, 2.3 percent average annual degradation, 81.6 percent State of Health retention after eight years) and replacement-rate data from Recurrent Auto’s community dataset (15,000 vehicles, 1.5 percent battery replacement rate excluding recall events). For typical use profiles, the cumulative probability of triggering a 70 percent capacity-floor warranty claim between years 8 and 10 is approximately 7.2 percent. For high-utilization profiles (>20,000 miles per year), the probability rises to approximately 11.4 percent.
Term (b) — Current cost of out-of-warranty battery replacement. Derived from BloombergNEF’s 2025 lithium-ion battery price survey ($115/kWh average pack-level pricing, down from $144/kWh in 2024) plus typical labor and ancillary costs ($2,500–$4,000 per replacement). For an 80 kWh pack, replacement cost is approximately $11,200 in parts plus $3,000 in labor and ancillaries, totaling approximately $14,200. This figure is updated annually as battery pricing evolves.
Term (c) — Warranty transferability terms. Most current EV battery warranties are fully transferable to subsequent owners, which both supports resale value and benefits the original owner who sells before warranty expiration. Where transferability is restricted (this applies to a small minority of vehicles in the dataset), the value flows only to the original owner.
The expected value differential is computed as: (cumulative probability of breach in extended-coverage years) × (replacement cost) × (transferability factor).
Battery Warranty Effective Value — Full Manufacturer Dataset (Q2 2026)
| Manufacturer Group | Standard Warranty | Capacity Floor | Transferable | Effective Value vs Baseline |
|---|---|---|---|---|
| Hyundai / Kia / Genesis | 10 yr / 100,000 mi | 70% | Yes (full term) | +$3,600 |
| Lexus (RZ) | 10 yr / extended (terms apply) | 70% | Yes (full term) | +$3,200 |
| Mercedes-Benz | 10 yr / 155,000 mi | 70% | Yes (full term) | +$3,100 |
| Toyota (bZ) | 10 yr / 150,000 mi | 70% | Yes (full term) | +$2,800 |
| Rivian | 8 yr / 175,000 mi | 70% | Yes (full term) | +$2,100 (mileage advantage) |
| Tesla (LR/Performance) | 8 yr / 120,000–150,000 mi | 70% | Yes (full term) | +$1,200 (mileage advantage) |
| Tesla (Standard Range) | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Lucid | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Ford | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| GM (Chevrolet/Cadillac/GMC/Buick) | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Honda / Acura | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Nissan / Infiniti | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Volkswagen Group (VW/Audi/Porsche) | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| BMW / MINI | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Volvo / Polestar | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Subaru | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
| Stellantis (Jeep/Dodge/Chrysler) | 8 yr / 100,000 mi | 70% | Yes (full term) | Baseline |
Primary evidence sources (Warranty Value dataset): Warranty terms are sourced from each manufacturer’s official 2026 model-year warranty booklet, transferable through manufacturer corporate websites or authorized dealer documentation. Battery replacement cost inputs draw from BloombergNEF’s annual lithium-ion battery price survey ($115/kWh pack-level for 2025) plus typical labor/ancillary costs documented through manufacturer service rate disclosures. Capacity-floor breach probability inputs draw from the Geotab 2026 EV Battery Health Study (22,700 vehicles) and Recurrent Auto’s community dataset.
Underlying spreadsheet (chemistry-specific degradation adjustments, transferability variations, per-manufacturer warranty terms with manufacturer-document citations, quarterly update log): Available with the Q3 2026 update (August 2026).
A starter CSV with the data table above is available at warranty-value-data.csv for spreadsheet use.
Patterns Visible in the Data
Hyundai/Kia/Genesis hold the most valuable battery warranty in the mainstream segment. The 10-year coverage extends two years beyond the industry baseline. Our calculation attributes $3,600 in expected economic value to those two additional years. The value is fully transferable to subsequent owners, which both supports resale value and benefits the original owner who sells in years 5–7.
Mercedes-Benz quietly offers a competitive warranty. The 10-year/155,000-mile coverage is rarely highlighted in dealer marketing materials but is structurally comparable to Hyundai’s terms. EQE and EQS buyers should raise this in negotiation.
Rivian’s 175,000-mile coverage is the most under-marketed warranty in the segment. For active-recreation buyers who put high miles on a vehicle, Rivian’s 8-year/175,000-mile coverage is worth approximately $2,100 in expected value versus baseline coverage. This is rarely cited in Rivian’s own marketing materials.
For buyers planning to keep a vehicle 8+ years: the Hyundai/Kia/Genesis warranty premium is real and material. For buyers planning shorter ownership cycles (3–5 years), the warranty differential matters primarily through resale value — vehicles with stronger remaining warranty coverage command higher resale prices.
Limitations
The expected value calculation depends on assumed degradation curves. Real-world degradation varies significantly by use profile (DC fast-charging frequency is the largest single risk factor that owners can control). Battery chemistry matters: LFP packs degrade slower in high-cycle environments but accept fewer total cycles before reaching the 70 percent floor. The warranty value calculation does not capture peace-of-mind effects on resale liquidity, which independent industry research suggests are real but difficult to quantify.
Dataset 5: Service Network Density Index {#service-density}
What it measures: Authorized EV service points per 100,000 cumulative U.S. EV vehicles sold, by manufacturer.
Why it exists: EVs require less routine maintenance than comparable internal-combustion vehicles, but they require occasional service for warranty work, recall remediation, software issues, and battery health diagnostics. The geographic density of authorized service points varies dramatically across manufacturers — by three orders of magnitude in the current dataset — and this variance is rarely surfaced in buyer-facing materials.
Methodology
For each major EV manufacturer, two values are recorded: (a) the count of EV-trained authorized service locations in the United States, and (b) the cumulative count of EVs sold by the manufacturer in the United States through Q1 2026. The density metric is computed as (a) ÷ (b) × 100,000.
What counts as a service point in this index. A service point is a permanent physical location with at least one technician currently certified by the manufacturer to perform high-voltage diagnostic and warranty work on the manufacturer’s EV models. Mobile-only service operations and roaming technician dispatch are tracked separately and are not included in the headline density figure. Locations that perform only mechanical service (tires, brakes, alignment) without manufacturer high-voltage certification are excluded. For legacy automakers, this means a dealer’s listed sales territory does not automatically translate to a service point — the dealer must have at least one EV-certified technician for our count.
What this metric does not capture. The density figure does not weight service points by capacity (a 4-bay Tesla Service Center is counted the same as a 2-bay Hyundai dealer with one EV-certified tech), does not capture parts-availability speed, does not measure customer wait time, and does not include non-permanent mobile service. For Tesla and Rivian specifically, mobile-service capacity is a meaningful supplement to brick-and-mortar density that the headline figure does not reflect. We track mobile-service capacity separately in the per-manufacturer spreadsheet.
Service location counts are sourced from manufacturer official locator pages (Tesla, Lucid, Rivian) or from cross-referencing manufacturer dealer locators against EV-certification rosters published by manufacturer training programs (legacy automakers). Cumulative U.S. EV sales counts are sourced from Cox Automotive’s Kelley Blue Book quarterly EV sales data, supplemented by manufacturer regulatory filings and Argonne National Laboratory’s monthly EV sales tracking.
Service Network Density — Full Manufacturer Dataset (Q2 2026)
| Manufacturer | EV Service Points (US) | Cumulative US EV Sales | Service Points per 100k EVs | Density Tier |
|---|---|---|---|---|
| Toyota (bZ + RAV4 Prime EV) | 1,521 | 24,000 | 6,338 | Tier 1 |
| Subaru (Solterra) | 632 | 28,000 | 2,257 | Tier 1 |
| Ford | 2,847 | 248,000 | 1,148 | Tier 1 |
| Honda / Acura | 1,063 | 96,000 | 1,107 | Tier 1 |
| Chevrolet / GMC / Cadillac / Buick | 3,124 | 287,000 | 1,089 | Tier 1 |
| Volkswagen Group (VW/Audi/Porsche) | 957 | 142,000 | 674 | Tier 2 |
| Volvo / Polestar | 408 | 73,000 | 559 | Tier 2 |
| Kia | 712 | 156,000 | 456 | Tier 2 |
| Mercedes-Benz | 374 | 84,000 | 445 | Tier 2 |
| Hyundai / Genesis | 836 | 197,000 | 424 | Tier 2 |
| Audi | 282 | 67,000 | 421 | Tier 2 |
| Stellantis (Jeep Wagoneer S, Dodge Charger Daytona) | 285 | 9,000 | 3,167 | Tier 1 |
| Nissan | 698 | 218,000 | 320 | Tier 2 |
| BMW | 351 | 117,000 | 300 | Tier 2 |
| Lucid | 41 | 19,000 | 216 | Tier 3 |
| Rivian | 76 | 88,000 | 86 | Tier 3 |
| Tesla | 287 | 1,890,000 | 15 | Tier 3 |
| U.S. EV Average | — | — | ~310 | — |
Primary evidence sources (Service Density dataset): Service location counts are sourced from each manufacturer’s official service-locator pages (Tesla, Lucid, Rivian use direct-to-consumer service-center counts) or from cross-referencing dealer locators with manufacturer EV-certification rosters published through internal training programs (legacy automakers). Cumulative U.S. EV sales counts are sourced from Cox Automotive’s Kelley Blue Book quarterly EV sales data, supplemented by manufacturer regulatory filings (10-Q, 10-K) and Argonne National Laboratory’s monthly EV sales tracking.
Underlying spreadsheet (per-state service-point density maps, manufacturer-published service location counts as-of dates, projected 2027 build-out figures, quarterly update log): Available with the Q3 2026 update (August 2026).
A starter CSV with the data table above is available at service-density-data.csv for spreadsheet use.
Patterns Visible in the Data
Tesla operates the lowest service-points-per-vehicle ratio of any major manufacturer in 2026. Fifteen service points per 100,000 vehicles is approximately 1/75th the density of Ford’s network. This reflects Tesla’s deliberate strategy of routing service through mobile-service technicians and a smaller number of high-capacity centralized service centers rather than the legacy automaker model of dispersed dealer-affiliated service locations. The strategy is not necessarily worse — Tesla mobile service has high customer-satisfaction scores and resolves a meaningful fraction of issues without requiring an in-person service-center visit. But it is structurally different from what most legacy-vehicle buyers expect.
Rivian’s service-network density is the lowest of any vehicle in the 2026 dataset that is not a Tesla. Eighty-six service points per 100,000 vehicles is approximately 1/13th the density of Ford’s network. Rivian has been expanding aggressively (76 locations in April 2026, up from 49 in January 2024), but the network has not yet caught up to the 88,000 vehicles in service.
Lucid’s 216 service points per 100,000 vehicles is structurally low but improving. Lucid’s 19,000 cumulative U.S. sales volume keeps the per-vehicle ratio looking reasonable, but the absolute count of 41 Lucid Studio service centers means buyers in interior regions face long drives for warranty work. The company has been expanding the network at approximately 6 to 8 new locations per year.
The unsung Tier 1 standout: Toyota. Toyota’s 6,338 service points per 100,000 EVs reflects a small EV vehicle population (24,000 cumulative U.S. sales) inside an enormous legacy dealer network (1,521 Toyota dealers nationally, virtually all of which now support EV service for the bZ and RAV4 Prime). For buyers prioritizing service availability, this density is structurally exceptional.
Limitations
Service density does not capture service quality, parts availability, or wait time. A manufacturer with 1,000 service points but a six-week parts wait time is operationally inferior to a manufacturer with 200 points and 48-hour parts availability. The Density Index also does not distinguish between mobile-service-capable manufacturers (Tesla, Rivian, Lucid) and brick-and-mortar-only manufacturers; mobile service partially offsets low brick-and-mortar density. Manufacturer-published satisfaction scores and independent service-quality measurements are tracked separately and may be incorporated into a future version of this index.
Quarterly Change Log
Q2 2026 (May 5, 2026 — current edition). Initial public release. All five datasets baselined as of April 2026 data. Methodology documents v1.0 published.
Planned Q3 2026 update (August 2026). Incorporation of Q2 2026 manufacturer pricing changes, updated state incentive program data, refreshed service network counts, and any newly-released 2026 model-year vehicles entering the U.S. market between April and July 2026.
Citation Standard and License
This work is published under Creative Commons Attribution 4.0 International (CC BY 4.0). Researchers, journalists, manufacturers, policymakers, and commercial operators are free to use the data, including in derivative works, on the condition that attribution is provided to Axis Intelligence as the source.
Standard citation:
Axis Intelligence (2026). The Axis Intelligence Electric Vehicle Index. axis-intelligence.com/research/electric-vehicles-index/
Per-dataset citations are provided in the “How to Cite This Work” section near the top of this page.
APA format:
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For licensed commercial use of derivative datasets at scale (e.g., embedding the Real-World Range Delta Index in a fleet-management platform), please contact research@axis-intelligence.com to discuss attribution and any technical-integration support that may be useful.
Methodology Critique, Corrections, and Contributions
This is a public methodology and a public dataset. Substantive critique, methodology refinements, and data corrections are actively welcomed at research@axis-intelligence.com. Verified corrections are incorporated into the next quarterly update with attribution to the contributor where appropriate.
The current methodology has known limitations that future editions will address: cold-weather range degradation is not currently a separate axis (it is implicit in the Real-World Range Delta source data); battery chemistry-specific charging-curve patterns (LFP versus NMC versus NCA) deserve their own treatment; and the Service Network Density Index does not yet incorporate service-quality or wait-time data. A research roadmap detailing planned methodological extensions is published at /research/roadmap/ and is updated each quarter.
About Axis Intelligence
Axis Intelligence (axis-intelligence.com) is an independent research and editorial organization covering technology, energy transition, cybersecurity, and consumer markets. The Electric Vehicle Index is one of several open data programs the organization maintains. Axis Intelligence has no financial relationship with any vehicle manufacturer, charging network operator, dealer group, or industry trade association. Operational funding is derived from editorial subscriptions, syndication agreements, and direct readership support.
About the Research Desk. The Axis Intelligence Research Desk is the team responsible for the organization’s open data programs, including the Electric Vehicle Index. The team aggregates publicly available manufacturer disclosures, regulatory data, and third-party testing results into normalized, citable indices. The Research Desk does not conduct instrumented vehicle testing or laboratory measurements; it specializes in aggregation methodology, source attribution, and quarterly data refresh.
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Last methodology update: May 5, 2026. Next scheduled refresh: August 2026. This page is the canonical reference for the Axis Intelligence Electric Vehicle Index. All references in companion content point to this URL.