Abstract
Research and/or Engineering Questions/Objective
The key objective of this paper is to identify and examine the existing electrical appliances in electric vehicles in line with the power consumption of the individual components and loading profile in order to create an advanced smart power management system targeting to optimise the power consumption of the on-board systems in real-time environment; therefore to increase the usability of electric vehicles (EV) through longer distance between recharges. Most researches have been done for powertrain energy optimisation with inadequate understanding of other appliances, whereas this paper is mainly focused on the on-board systems and their interactions with elimination of the powertrain control.
Methodology
Methodology of this paper includes estimating the power consumption for the stochastic driving mode, developing the load control algorithm, and implementing the real-time optimisation strategy with the explanation of its importance and the benefits of a new smart energy management approach in terms of usability and energy consumption of electric vehicles. Loading profile of the systems will be developed from previous research of RMIT Vietnam Centre of Technology and existing research papers. The simulation test will be performed on the obtained loading profiles of various appliances and the outcome of the approach will be analysed in comparison with existing approaches for on-board power management.
Results
In this paper, power consumption and distance on a single charge of a middle size electric vehicle will be profiled as a function of the on-board systems. The power optimisation strategy will be applied to decrease the power consumption and increase the distance on a charge for both hot and cold climate conditions, as the ambient temperature has a significant impact on the operation of the on-board systems. Real-time optimisation approach will be presented as a way to manage the energy consumption.
Limitations of this study
This study has several limitations. First and the most serious one is the exclusion of powertrain system from the optimisation strategy. The reason to do this is to unite the appliances and manage small systems with different variables rather than concentrate on the powertrain as the most energy-consuming device. The second limitation is the testing cycle, which is going to be used. On-board systems usage is not listed clearly in the testing procedures for the available driving cycles, as their main purpose is to test the drivetrain performance and fuel consumption, whilst this study will not include the powertrain system in the governance strategies.
What does this paper offer that is new in the field including in comparison to the other work by the authors?
The real-time optimisation approach for the energy management system of the on-board appliances is a new approach as the existing studies mainly concentrate only on the powertrain management.
Conclusion
New approach for the power management system was implemented and tested. The algorithm was based on the asynchronous logic operations to satisfy stochastic nature of the energy consumption in EV.
KEYWORDS : Asynchronous Logic, Electric Vehicles, Energy Consumption Optimisation