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Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

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  • Pier Giuseppe Anselma

    (Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Torino, Italy
    Center for Automotive Research and Sustainable Mobility (CARS), Politecnico di Torino, 10129 Torino, Italy)

Abstract

Assessing the potential of advanced driver assistance systems requires developing dedicated control algorithms for controlling the longitudinal speed of automated vehicles over time. In this paper, a multiobjective off-line optimal control approach for planning the speed of the following vehicle in adaptive cruise control (ACC) driving is proposed. The implemented method relies on the principle of global optimality fostered by dynamic programming (DP) and aims to minimize propelling energy consumption and enhance passenger comfort. The powertrain model and onboard control system are integrated within the proposed car-following optimization framework. The retained ACC approach ensures that the distance between the following vehicle and the preceding vehicle is always maintained within allowed limits. The flexibility of the proposed method is demonstrated here through ease of implementation on a wide range of powertrain categories, including a conventional vehicle propelled by an internal combustion engine solely, a pure electric vehicle, a parallel P2 hybrid electric vehicle (HEV) and a power-split HEV. Moreover, different driving conditions are considered to prove the effectiveness of the proposed optimization-driven ACC approach. Obtained simulation results suggest that up to 22% energy-saving and 48% passenger comfort improvement might be achieved for the ACC-enabled vehicle compared with the preceding vehicle by implementing the proposed optimization-driven ACC approach. Engineers may adopt the proposed workflow to evaluate corresponding real-time ACC approaches and assess optimal powertrain design solutions for ACC driving.

Suggested Citation

  • Pier Giuseppe Anselma, 2021. "Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort," Energies, MDPI, vol. 14(10), pages 1-28, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2897-:d:556438
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    References listed on IDEAS

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    Cited by:

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    2. Sara Luciani & Andrea Tonoli, 2022. "Control Strategy Assessment for Improving PEM Fuel Cell System Efficiency in Fuel Cell Hybrid Vehicles," Energies, MDPI, vol. 15(6), pages 1-17, March.
    3. Pier Giuseppe Anselma, 2022. "Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health," Energies, MDPI, vol. 15(5), pages 1-25, February.
    4. Antonio Capuano & Matteo Spano & Alessia Musa & Gianluca Toscano & Daniela Anna Misul, 2021. "Development of an Adaptive Model Predictive Control for Platooning Safety in Battery Electric Vehicles," Energies, MDPI, vol. 14(17), pages 1-14, August.

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