Energy Resource Costs of Military Driver Training Using the BYD T5 and GAZ-66 and the Potential for Solar Energy Supply of the Electric Vehicle Fleet
Abstract
Purpose. To quantitatively assess the energy resource costs of practical training for category C and C1 drivers using the BYD T5 electric truck compared with the GAZ-66, and the potential for meeting the corresponding energy demand through on-site solar generation.
Methods. A calculation-analytical model based on the current regulatory framework was applied. The model considers the amount of practical driving training, parameters of Exercise No. 5, energy resource costs per trainee, training fleet capacity, and payback period. Sensitivity analyses were performed for the electricity tariff, specific energy consumption, and average driving speed.
Results. Under the baseline parameters, energy resource costs amount to UAH 9,809 per trainee for the GAZ-66 and UAH 1,111 for the BYD T5, representing an 8.8-fold cost advantage for the electric truck. For 100 trainees, the estimated savings amount to approximately UAH 870,000. The payback threshold for the BYD T5 is 257 trainees, while the payback period for a complete system comprising six vehicles and the energy complex is 7.3 years. A 29.25 kWp solar array could potentially meet the energy demand for training up to 312 trainees annually.
Theoretical implications. A combined approach integrating a training-process cost model with an assessment of PV–BESS energy supply for the training fleet is proposed.
Practical implications. The results can support decisions on re-equipping training fleets and investing in on-site energy generation.
Originality/value. The study combines an assessment of military driver training costs using electric vehicles with an evaluation of the potential for solar energy supply.
Limitations/future research. The model does not constitute a comprehensive TCO/LCC assessment. Further research should address the complete training-exercise profile, TCO/LCC, and monthly solar generation profiles.
Article type: Calculation-analytical article (applied modelling study).
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