Vehicle acceleration modeling with constant power: manual, automatic and electric transmission

This paper presents the acceleration process of vehicles with different transmissions. The focus is on accurately modelling this process and comparing the models with real-world test data. Constant power equations are developed for different transmissions, including electric, manual, and automatic transmission. The paper analyses the development of mathematical models for vehicle acceleration, taking gear change time into account and aiming to represent real road conditions accurately. This analysis examines the phenomenon of vehicle acceleration on flat asphalt surfaces, as the used accelerometer is automatically compensated for the gradient and provided results for a straight road with no gradient, which serves as a foundational component for traffic simulations. These simulations are essential in reconstructing various vehicular dynamics encountered in urban areas, such as rear-end collisions when driving in a column or vehicles accelerating through intersections. Researchers can effectively replicate real-world scenarios by comprehensively understanding vehicle acceleration, offering invaluable insights for accident investigation, safety assessment, and other related fields. The paper compares theoretical models with real-world test data. The model has been expanded with an algorithm that enables the determination of model parameters from the measured acceleration values. The results indicate that the measured acceleration from initial speed to constant velocity for different transmissions is similar to the theoretical curve. On average, the ratio of nominal engine power to power consumption for acceleration to constant velocity is approximately 50% of the nominal P/m value and 80% of the maximum surface load. The vehicle and driver characteristics can be assumed to account for approximately 50% of the nominal P/m value and 80% of the maximum surface load. It is important to note that these results cannot be generalized as the outcomes may vary depending on how the driver accelerates.