  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 braking and
ACCS based on which the performance of PGACCS and regenerative braking is
evaluated; the PnG energy performance is optimized and the effect of
regenerative braking on PnG energy performance is evaluated. As a result of PnG
optimization, the PnG operation in the PGACCS could cut down 28.3% energy cost
of the EV compared to the CC operation in the traditional ACCS which verifies
that PnG is an effective energy-saving strategy for EV and PGACCS is a
promising option for EV.
