This study presents an empirical fleet-level assessment of 110 autonomous-range trolleybuses using anonymized records collected over 12 months. The dataset comprises 40,150 vehicle-day operating records, 40,150 energy records, 3960 pack-month SOH records, and 584 maintenance, failure, and downtime events. Outcomes are reported in absolute units: RUB/km for LCC, kg CO2-eq/km for ELC, events per 100,000 km, and downtime hours per 10,000 km. Autonomous operation accounted for 24.5% of mileage. Average net energy consumption was 1.520 kWh/km, whereas mode-distributed gross energy was 1.521 kWh/km in contact-supply mode and 1.752 kWh/km in autonomous mode. The daily-energy model achieved a full-sample fit of R2 = 0.860 and MAPE = 8.119%. Validation of vehicle-grouped data using the generated dataset showed R2 = 0.842 and MAPE = 8.74%. Mean SOH decreased from 89.98% to 85.94%, accompanied by higher internal resistance. In the central 6.5-year scenario, diagnostic-gated strategy B2 reduced estimated LCC from 29.52 to 26.16 RUB/km. The event-weighted control effect by RPN decreased from 125.4 to 80.4 (35.9%). Baseline ELC decreased only from 0.6646 to 0.6594 kg CO2-eq/km because operational electricity dominated the total. The contribution is an observation-linked framework that integrates vehicle-day operation, pack-month diagnostics, and event-level maintenance data to compare cost, emissions, and risk under explicit battery-eligibility and service-coverage constraints. The novelty is therefore the empirical, observation-level coupling and joint calibration of existing energy, battery-condition, life-cycle, and reliability methods within one auditable fleet workflow, rather than the introduction of a new standalone degradation or reliability model.
Malozyomov et al. (Wed,) studied this question.