Intelligent energy management control systems for autonomous vehicles
Autonomous vehicles (AVs) have been envisioned to increase vehicle safety, primarily via the reduction of accidents. However, their design could also affect the vehicle travel demand and energy consumption. Both vehicle travel demand and energy consumption can be considered a complex system because they are subject to continuous fluctuations from environmental conditions and driver behaviour. Intelligent control systems have been proven to be competent for regulating highly complex and nonlinear procedures, which account for intermittent disturbances. This thesis concentrates on developing Intelligent Energy Management Control Systems (IEMCS) to enhance the fuel efficiency of AVs. Additionally, modeling and simulation are utilized to improve their effectiveness and to reduce their development and evaluation times. An AV can be powered by hybrid electric engines in a Parallel Hybrid Electric Autonomous Vehicle (PHEAV) and an internal combustion engine in a Conventional Autonomous Vehicle (CAV). Therefore, in this thesis, the proposed IEMCS are constructed to reduce fuel consumption for CAVs and PHEAVs by using the Road Power Demand model (RPD). The RPD model utilizes three impact factors (i) Environment conditions, (ii) Driver behavior, and (iii) Vehicle specifications (EDV) that are involved in vehicle energy consumption. The proposed IEMCSs are simulated and evaluated under the standard Highway Fuel Economy Test Cycle (HWFET). This test cycle is considered under the dynamic driver behavior, the real-world parameters associated with vehicle specifications and artificial environmental conditions. The simulation results are presented and discussed. It is demonstrated that the proposed intelligent energy management systems can reduce the fuel consumption without sacrificing the performance of the vehicle.
- Record URL:
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Supplemental Notes:
- PhD thesis
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Authors:
- Phan, D V
- Publication Date: 2021-2
Language
- English
Media Info
- Pagination: 1 file
Subject/Index Terms
- TRT Terms: Advanced vehicle control systems; Advanced vehicle control systems; Automated vehicle control; Autonomous vehicles; Electric vehicles; Energy consumption; Fuel consumption; Hybrid vehicles; Test procedures; Vehicle tests
- Geographic Terms: Melbourne, Victoria
- ATRI Terms: Advanced vehicle control systems (AVCS); Autonomous vehicle; Electric vehicle; Energy consumption; Fuel consumption; Hybrid vehicle; Vehicle testing
- ITRD Terms: 9011: Design (overall design)
- Subject Areas: Energy; Vehicles and Equipment; I91: Vehicle Design and Safety;
Filing Info
- Accession Number: 01778803
- Record Type: Publication
- Source Agency: ARRB Group Limited
- Files: ITRD, ATRI
- Created Date: Aug 6 2021 4:37PM