Virtual simulations of electrical vehicle performance help to optimize vehicle design, by studying and predicting the effects of parameter variations on the vehicle performance, in order to find an optimum balance between the cost and benefit of design decisions. In this work, the development of a virtual platform to evaluate the performance of an electrical vehicle is presented and applied to the study of public urban transportation. The aim is to analyze the requirements and optimize specifications for a light weight, energy efficient, autonomous vehicle without energy supply along the trajectory, except in the stations.
Virtual platforms for vehicle performance have been developed before, and in many cases characteristic velocity profiles are used as a reference, according to the traffic environment in which the vehicle will operate. Vehicle analysis and design is focused on feasibility of the vehicle to be able to follow the prescribed velocity profile.
In the present study, the evaluation is instead based on the cost/benefit relationship for an urban transport vehicle on traffic-free trajectories, enabling to adjust and optimize the velocity profiles in order to optimize the energy use while minimizing travel time. Therefore, the virtual platform is focused on the calculation of the net energy usage, the travel time and the system cost corresponding to an electrical vehicle with different battery and ultra-capacitor energy storage capacities, regeneration and storage of brake energy and an automatic governor for autonomous vehicle control.
The influence of design parameters, such as the installed motor power, energy storage capacity, vehicle weight, passenger load and vehicle control strategy on the time schedule and energy efficiency is studied. However, the effort does not aim for a straight forward optimization of efficiency or minimization of travel time. In fact, energy optimization often conflicts with the travel time optimization. Therefore, both are analyzed simultaneously in order to assist in the search for an optimum compromise. In addition, the results are interpreted in terms of the overall obtained benefits of travel time reduction or optimization of the energy use, in contrast with the corresponding increment of the investment cost of the vehicle related to the implementation of the studied parameter variation. Specific trajectory profiles, including height profiles can be defined for optimization of the vehicle system for application in specific locations with specific geographic conditions.
Modeling and Control Strategy for Hybrid Electrical Vehicle
