Definition of a Rule-Based Energy Management Controller for the Simulation of a Plug-In Hybrid Vehicle Using Power and On-Board Measured Data

Author:

Doulgeris Stylianos1,Tsakonas Georgios1,Dimaratos Athanasios1,Kontses Dimitrios1,Samaras Zissis1

Affiliation:

1. Aristotle University of Thessaloniki

Abstract

<div class="section abstract"><div class="htmlview paragraph">Vehicle powertrain electrification is considered one of the main measures adopted by vehicle manufacturers to achieve the CO<sub>2</sub> emissions targets. Although the development of vehicles with hybrid and plug-in hybrid powertrains is based on existing platforms, the complexity of the system is significantly increased. As a result, the demand for testing during the development and calibration stages is getting significantly higher. To compensate that, high-fidelity simulation models are used as a cost-effective solution. This paper aims to present the methodology followed for the development of a rule-based energy management controller for a plug-in hybrid electric vehicle (PHEV), and to describe the experimental campaign that provided the necessary input data. The controller is implemented in a vehicle simulation model that is parametrized to replicate the real operation of the vehicle. Using such a model it is possible to carry out virtual tests, aiming towards energy management optimization and efficiency improvement. The main target of the experimental campaign and the data analysis was to define the operational and energy management strategy of the vehicle using a back engineering approach. Laboratory tests were performed under legislated cycles and real-world driving profiles. In addition to the standard fuel consumption and emissions measurements, a power analyzer was implemented for the measurement of the currents and voltages, which were then used for the electric power calculation of the main powertrain components (electric machine and high voltage battery). This calculation allowed the evaluation of the power flow within the powertrain and the individual components. In addition, on-board data, such as battery state of charge, engine torque and total fuel and energy consumption (provided by the on-board fuel consumption monitoring measurement -OBFCM- system) were recorded from the on-board diagnostic (OBD) port. All the recorded data and the observations made during the experimental campaign were used to define the appropriate rules for the developed controller.</div></div>

Publisher

SAE International

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