Energy minimization for an electric bus using a genetic algorithm

Abstract

Background and methods: This paper addresses, in simulation, energy minimization of an autonomous electric minibus operating in an urban environment. Two different case studies have been considered, each involving a total of 10 different 2?km bus routes and two different average speeds. In the proposed method, the minibus follows an optimized speed profile, generated using a genetic algorithm. Results: In the first case study the vehicle was able to reduce its energy consumption by around 7 to 12% relative to a baseline case in which it maintains a constant speed between stops, with short acceleration and deceleration phases. In the second case study, involving mass variation (passengers entering and alighting) it was demonstrated that the number of round trips that can be completed on a single battery charge is increased by around 10% using the proposed method.

Vehicle Cycle Hierarchization Model to Determine the Order of Battery Electric Bus Deployment in Public Transport

“…In [41], deep learning methods were adopted when estimating BEB energy consumption on real-world data in the Polish municipality of Jaworzno. A genetic algorithm for the energy consumption minimization of BEBs was developed in [42], and a machine learning algorithm is applied in [43] for the same purpose. Wei et.…”

Genetic Algorithm-Based Energy-Saving Control Strategy of Vehicle Drive

“…It is a calculation method that simulates Darwin's theory of evolution and genetics. The algorithm has the following characteristics [14]:…”

“…The optimization variables selected in this study are the gear ratios of the transmissions that change the braking force and the gear ratio of the main reducer. The design idea is: (14) In the above matrix, is the gear ratio of the reducer, is the gear ratio of each gear of the transmission, n is the number of gears of the transmission, and T is the vehicle torque.…”

Evaluation of Non-Classical Decision-Making Methods in Self Driving Cars: Pedestrian Detection Testing on Cluster of Images with Different Luminance Conditions

“…Previous studies presented that energy minimization is a critical area of autonomous transport system development, where advanced longitudinal and lateral vehicle control methods will play a key role in achieving expected results [1][2][3][4][5][6][7]. Conversely, numerous research papers propose to improve the efficiency of the vehicle control process through the development of sensor systems and image detection methods [8][9][10][11].…”