In addition to the widely recognized benefits of reducing carbon emissions and protecting the environment, the authors believe that bus electrification has potential advantages in enhancing driving safety, improving passenger comfort, and reducing driver fatigue—areas that have not yet been sufficiently studied and emphasized. Safety and comfort are fundamental objectives in the continuous development of transportation systems. They are directly and closely related to both passengers and drivers and are among the top priorities when individuals choose their mode of transportation. Therefore, these aspects deserve broader and more in-depth attention and research. This study aims to identify the potential advantages of route bus electrification in terms of safety and comfort. The results of a passive experiment on the speed profile of buses operating on actual routes are presented here. Firstly, we focus on the acceleration/deceleration at the starting/stopping stops, specifically for regular-route buses, and obtain the following information: I. Starting acceleration from a bus stop is particularly strong in the second half of the acceleration process, being suitable for motor-driven vehicles. II. The features of the stopping deceleration at a bus stop are “high intensity” and “low dispersion”, with the latter enabling the refinement of regenerative settings and significantly lowering electricity economy during electrification. And we compare the speed profile of an electric bus with those of a diesel bus and obtain the following information: III. Motor-driven vehicles offer the advantages of “high acceleration performance” and “no gear shifting”, making them particularly suitable for the high-intensity acceleration required when route buses depart from stations. This not only simplifies driving operations but also enhances lane-changing safety. And by calculating and analyzing the jerk amount, we could quantitatively demonstrate the comfortable driving experience while riding on this type of bus where there is no shock due to gear shifting. IV. While the “high acceleration performance” of motor-driven vehicles produces “individual differences in the speed change patterns”, this does not translate to “individual differences in electricity consumption”, owing to the characteristics of this type of vehicle. With engine-driven vehicles, measures such as “slow acceleration” and “shift up early” are strongly encouraged to realize eco-driving, and any driving style that deviates from these measures is avoided. However, with motor-driven vehicles, the driver does not need to be too concerned about the speed change patterns during acceleration. This characteristic also suggests a benefit in terms of the electrification of buses.

This study aims to develop a theoretical formula to help bus operators easily predict electricity consumption while introducing a certain type of electric bus on a predetermined route. The formula requires vehicle-side information (such as air resistance coefficient, rolling resistance coefficient, vehicle weight, powertrain efficiency, kinetic energy recovery rate, auxiliary equipment electricity consumption, and other vehicle-related data) for construction and road-/operation-side information (such as average driving speed, number of starts and stops, road gradients, and other road-/operation-related data) for prediction. First, herein, as a basic study to construct the theoretical formula, a developed electric bus and its vehicle electricity consumption simulator are employed. We then perform a comparative analysis considering the comparison of loss between the actual operation on public roads and the assumed constant velocity when running on flat roads. Next, we develop theoretical equations for the generalization of velocity and gradient changes and simplified modeling of electricity consumption prediction. Considering the burden of information collection on operators, we categorize it into three stages. In this paper, we first organize the minimum necessary road-/operation-side information (route/operational indicators). Next, we propose a theoretical formula for electricity consumption prediction constructed based on vehicle-side information. Finally, we validate the validity and accuracy of the constructed formula using electric buses and their on-road operational data that we developed earlier. The verification results showed that, after obtaining vehicle-side and road-/operation-side information, the theoretical formula constructed in this study achieved an electricity consumption prediction with an average error of 6% (high-accuracy method). This result demonstrates the practicality of using the theoretical formula to predict the electricity consumption/range of electric buses operating on specific routes.

In this study, we focused on the eco-driving of electric vehicles (EVs). The target vehicle is an electric bus developed by our research team. Using the parameters of the bus and speed pattern optimization algorithm, we derived the EV’s eco-driving speed pattern. Compared to the eco-driving of internal combustion engine vehicles (ICVs), we found several different characteristics. We verified these characteristics with actual vehicle driving test data of the target bus, and the results confirmed its rationality. The EV’s eco-driving method can improve electricity consumption by about 10–20% under the same average speed.