Open Research Hub.
Empirical datasets & models 2010–2026.
Peer-auditable datasets on Nordic automotive fleet aging, rubber hardening contact physics, municipal crash severity, and 11-year road weather telemetry. Precomputed using Koneisto Core Go turbines.
Nordic Fleet Longitudinal Dataset & Models
Annual benchmarks (FI vs. SE), vehicle age mileage decay, tread wear time, and Shore A hardening matrix.
@dataset{pelkonen_2026_nordic_fleet_tyres,
author = {Pelkonen, Tommi},
title = {{Nordic Vehicle Fleet Ageing and Tyre Safety 2010--2026: The Secondary Car Tyre Trap, Longitudinal Comparison, and Polymer Hardening Dynamics}},
year = 2026,
month = sep,
publisher = {Zenodo},
version = {1.0.0},
url = {https://rengasrepo.fi/tutkimus},
note = {DOI pending (Zenodo) / Open Science Dataset (CC BY 4.0)}
}# Suomen ja Ruotsin rengaskannan aikasarja-analyysi 2010-2026 (Python)
import pandas as pd
import json, urllib.request
# 1. Haetaan 16 vuoden vertailuaineisto
url = "https://rengasrepo.fi/data/suomen_rengaskanta_aikasarja_2010_2026.json"
req = urllib.request.urlopen(url)
data = json.loads(req.read().decode('utf-8'))
# 2. Aikasarjataulukko (Suomi vs. Ruotsi)
df_years = pd.DataFrame(data['yearly_benchmarks'])
print("--- Suomen ja Ruotsin vertailu 2010 vs 2026 ---")
print(df_years[df_years['year'].isin([2010, 2018, 2026])][[
'year', 'fi_fleet_age', 'se_fleet_age', 'fi_poor_tires_pct', 'se_poor_tires_pct'
]].to_string(index=False))
# 3. Kakkosauton rengasloukku (ajosuoritteen aleneminen vs. kulumisaika)
df_models = pd.DataFrame(data['vehicle_age_models'])
print("\n--- Auton ikäluokkamalli (kulumisaika & Shore A) ---")
print(df_models[df_models['vehicle_age'].isin([0, 5, 10, 15, 20])][[
'vehicle_age', 'annual_km', 'tread_wear_years_6mm', 'shore_a_winter', 'epr_ratio_pct'
]].to_string(index=False))
Four Core Findings from the 2010–2026 Fleet Study
Why older cars are not driven on bald tyres, but rather on dangerous, glass-hard aged rubber.
Nordic Fleet Gap is Growing Wider
In 2010, the age gap between Finland and Sweden was 1.9 years. By 2026, it expanded to 2.8 years. Swedish cars scrap at 18.5 years; Finnish cars remain in traffic until an average of 22.8 years, causing a massive structural delay in tyre renewals.
Tread Outlives Rubber Chemistry
A 15-year-old secondary vehicle averages only 5,000 km per year (winter ~2,350 km). Wearing down 6 mm of winter tread takes 19.1 years. Drivers inspect legal depth (5 mm) while rubber elasticity is long gone.
The Tyre Set Cost Barrier
A premium tyre set (€650) represents 43% of the value of a 15-year-old car (€1,500) and 91% of a 20-year-old car (€700). This economic parity mathematically discourages premature replacements.
Micro-Hysteresis Friction Collapse
Plasticizer loss and oxidative cross-linking increase winter rubber hardness from 54 Shore A to over 78 Shore A. The rubber behaves like hard wood or a dried-out eraser, sliding across ice micro-asperities instead of gripping.
16-Year Longitudinal Benchmark (Finland vs. Sweden)
Extracted from verified regulatory records (Traficom, Trafikanalys, OTI, VTI).
| Year | FI Fleet Age | SE Fleet Age | FI Scrap Age | FI Poor Tyres % | SE Poor Tyres % | FI Studded % | SE Studded % |
|---|---|---|---|---|---|---|---|
| 2010 | 11.8 v | 9.9 v | 20.1 v | 13.4 % | 5.6 % | 87.5 % | 52.0 % |
| 2014 | 12.0 v | 10.1 v | 20.6 v | 11.9 % | 5.2 % | 86.0 % | 48.0 % |
| 2018 | 12.2 v | 10.2 v | 21.2 v | 10.3 % | 4.9 % | 84.5 % | 44.0 % |
| 2022 | 12.8 v | 10.9 v | 21.9 v | 8.4 % | 4.7 % | 83.0 % | 40.5 % |
| 2024 | 13.1 v | 11.8 v | 22.2 v | 7.6 % | 4.6 % | 82.2 % | 39.0 % |
| 2026 | 13.5 v | 12.3 v | 22.5 v | 7.1 % | 4.5 % | 81.5 % | 37.8 % |
Mathematical Equations of Fleet Decay & Polymer Hardening
Formal equations used by the Koneisto Core turbine to model vehicle mileage decay, tread wear time, Shore A hardening, and contact mechanics.
Models exponential mileage drop as vehicle age a increases. At 15 years, annual driving drops to ~5,800 km (winter ~2,350 km).
With D_usable = 5.0 mm and w_rate = 0.11 mm/1,000 km, wearing out winter tread takes 19.1 years on a 15-year-old vehicle.
Initial S_0 = 54 A, oxidative hardening potential ΔS = 26 A, k_ox = 0.18. Rubber reaches 77 A at 10 years and 80 A at 15 years.
Ice grip depends on micro-hysteresis. As storage modulus E' escalates from hardening, hysteresis collapses, dropping ice friction by over 60%.
Explore the Vehicle Fleet Age Simulator & Tactile Thumb Test
Test any vehicle age (0–20 years) dynamically, see the exact Shore A ice grip drop, and read the full investigative report on Finnish tyre risks.
All calculation models and time series published on Rengasrepo are openly accessible under Creative Commons (CC BY 4.0). We do not accept sponsored product placements or commercial tyre marketing claims. Primary data sources include Traficom, Statistics Finland, SCB, Trafikanalys, Onnettomuustietoinstituutti (OTI), VTI, Autonrengasliitto ry, and the Finnish Meteorological Institute (FMI).