A Theo-Practical Methodology for Series Hybrid Vehicles Evaluation and Development

This paper presents an integrated experimental and simulation investigation which is conducted on a series hybrid electric vehicle. The mathematical model is simulated in two distinct environments; MATLAB/Simulink and GT-Suite. An experimental test rig is devised in order to measure the vehicle performance including wheeled-chassis dynamometer. Components consumed powers, vehicle speed, engine revolution, fuel consumption and consumed energies are all measured in real time and the results are used to verify the numerical modelling work. For optimizing the performance of the vehicle, a rule based control algorithm is proposed and applied to the model using Stateflow environment. Many sequential-decision logic-based rules are graphical coded to operate the internal combustions engine at its most fuel efficient modes. An in-house auto-driver is developed in order to implement the proposed rule-based algorithm through hardware-in-the-loop (HIL) simulation during different standard drive cycles. The auto-driver is aimed to automate the process of measuring the efficiency of the vehicle under different driving conditions. The tests results clearly show that, the overall vehicle efficiency is improved including a reduction in trip costs depending on driving conditions.

• Record URL:
  https://doi.org/10.4271/2017-01-1169
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • Ali, Ahmed M
  • Sharaf, Alhossein Mostafa
  • Kamel, Hesham
  • Hegazy, Shawky
• Conference:
  • WCX™ 17: SAE World Congress Experience
  • Location: Detroit Michigan, United States
  • Date: 2017-4-4 to 2017-4-6
• Publication Date: 2017-3-28

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 13p
• Serial:
  • SAE Technical Paper
  • Publisher: Society of Automotive Engineers (SAE)
  • ISSN: 0148-7191
  • EISSN: 2688-3627
  • Serial URL: http://papers.sae.org/

Subject/Index Terms

• TRT Terms: Algorithms; Dynamometers; Fuel conservation; Fuel consumption; Hybrid vehicles; Mathematical models; Methodology; Optimization; Simulation; Vehicle performance
• Subject Areas: Energy; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01684369
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 2017-01-1169
• Files: TRIS, SAE
• Created Date: Mar 30 2017 10:24AM