A Pulse-and-Glide-driven Adaptive Cruise Control System for Electric Vehicle
Zhaofeng Tian, Liangkai Liu, Weisong Shi

TL;DR
This paper introduces a pulse-and-glide-driven adaptive cruise control system for electric vehicles, demonstrating significant energy savings by integrating PnG with ACCS and optimizing it using advanced algorithms.
Contribution
It presents a novel PGACCS model that combines pulse-and-glide strategy with adaptive cruise control for EVs and verifies its energy efficiency through simulation and optimization.
Findings
PnG reduces EV energy cost by 28.3% compared to traditional cruise control.
Optimized PnG operation enhances energy savings in EVs.
Regenerative braking further improves energy efficiency in the proposed system.
Abstract
As the adaptive cruise control system (ACCS) on vehicles is well-developed today, vehicle manufacturers have increasingly employed this technology in new-generation intelligent vehicles. Pulse-and-glide (PnG) strategy is an efficacious driving strategy to diminish fuel consumption in traditional oil-fueled vehicles. However, current studies rarely focus on the verification of the energy-saving effect of PnG on an electric vehicle (EV) and embedding PnG in ACCS. This paper proposes a pulse-and-glide-driven adaptive cruise control system (PGACCS) model which leverages PnG strategy as a parallel function with cruise control (CC) and verifies that PnG is an efficacious energy-saving strategy on EV by optimizing the energy cost of the PnG operation using Intelligent Genetic Algorithm and Particle Swarm Optimization (IGPSO). This paper builds up a simulation model of an EV with regenerative…
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Taxonomy
TopicsVehicle emissions and performance · Electric Vehicles and Infrastructure · Traffic control and management
