The quality of pavements in rural roads in India is often inconsistent. Rural roads are often prone to damage due to heavy monsoon rains, inadequate drainage systems, and the use of substandard materials during construction result in pavement distress. Although a lot of research studies were conducted for battery electric vehicle energy consumption modeling, driving cycle construction and eco-driving strategies exists, there is a lack of research on the influence of pavement condition index (PCI). This paper estimates the best curve estimation model for PCI, driving characteristics parameters, and equivalent carbon dioxide emissions of Battery Electric Vehicle (BEV) on rural two-lane highways. The data collection includes driving data, energy consumption, and pavement distress density. The estimated curve functions showed that the parameters exhibited a nonlinear relationship. Road segments with extremely poor (PCI 26–40) and serious (PCI 11–25) conditions exhibited higher EV energy consumption and increased emissions. In contrast, poorly maintained segments with minor rutting and raveling did not affect emissions significantly. Maintaining a PCI between 48 and 87 was associated with the lowest equivalent CO \(_2\) equivalent emissions, achieving an optimal value of 88.85 gCO \(_2\) eq/km (equivalent carbon dioxide emissions).