Abstract
Minimum energy consumption with maximum comfort driving experience defines the ideal human mobility. Recent technological advances in most highly automated driving systems on electric vehicles with regenerative braking system not only enhance the safety and comfort level but also present a significant opportunity for automated eco-driving. This research focuses on the longitudinal eco-driving considering the coordinated control for 4WD intelligent electric vehicles. The intelligent electric vehicle framework with 4-wheel hub motors is established and the intention-aware longitudinal automated driving strategy for overall traffic situation levels is proposed. Further, the coordinated control strategy arbitrates the control mode basing on the traffic situation level and distributes braking forces between the electronic hydraulic braking system and the cooperative regenerative auxiliary braking system. The proposed strategy is verified in the co-simulation environment and field test respectively. Test results show optimal control effects in overall traffic situation levels and an enhanced energy recycling efficiency.
Highlights
Consumption of unrenewable fuels and critical pollution, such as global warming, unexpected climate changes and unprecedented amounts of air pollution, have caused both energy and environmental issues [1]
RELATED WORK Related work about Intelligent Electric Vehicles (IEVs) focuses on the vehicle framework considering physical states and dynamic characteristics of key assemble models, longitudinal auto-driving strategies in various kinds of traffic situation levels and the coordinated control strategy between the electronic hydraulic braking system and the cooperative regenerative braking system
WORK Given system requirements of IEVs, a coordinated control based longitudinal eco-driving for 4WD intelligent electric vehicles is proposed in this paper
Summary
Consumption of unrenewable fuels and critical pollution, such as global warming, unexpected climate changes and unprecedented amounts of air pollution, have caused both energy and environmental issues [1]. With respect to many previous studies on intelligent vehicles which tend to oversimplify or even ignore the co-driving technology with the vehicle-traffic interaction, the intention-aware integrated driving strategy for overall traffic situation levels has attracted much recent attention from all over the world [3], [4]. How to integrate the energy optimization during the longitudinal eco-driving process and vehicle safety under complex scenarios with uncertainties is a formidable challenge To overcome this problem, the traffic situation should be estimated in real time and an intention-aware longitudinal automated driving strategy applicable to overall traffic situation levels needs to be established [8].
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