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Comprehensive energy footprint benchmarking of commercial electrified powertrains

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  • Anwar, Hamza
  • Vishwanath, Aashrith
  • Ahmed, Qadeer
  • Chunodkar, Apurva

Abstract

This work presents a comprehensive energy management framework applied to electrified commercial powertrains with in-depth energy footprint analysis. We use our recently proposed algorithm, validated real-world powertrain system models, and Pareto-optimal analysis to optimize fuel consumption and harmful pollutant emissions. The approach involves dynamic optimization of 13 states and 4 control levers capturing complex subsystem interactions in parallel P2 and series range-extender commercial medium-duty electrified trucks. These subsystems exhibit vehicular (eco-driving), thermal, electrical, and mechanical dynamics at different time scales, and contain kinematic and combinatorial constraints, integer- and real-valued variables, interpolated look-up tables, and data maps. A Pareto-optimal solution is found by carefully optimizing fuel and NOx emissions to understand the energy footprint. Presented results exhibit rich powertrain behavior to unearth up to 6% improvement in energy demand, 2% in fuel economy and 18% in pollutant NOx reduction when compared to Dynamic Programming baseline from a coarsely modeled powertrain system. Furthermore, internal energy flow in the powertrains is analyzed to benchmark the optimal energy consumption and realize the multi-objective trade-off. Finally, a transient study problem is presented comparing cold versus warm after-treatment start conditions. It optimizes engine switching, eco-driving, and powersplit controls revealing adequate dynamic response and complex system interactions.

Suggested Citation

  • Anwar, Hamza & Vishwanath, Aashrith & Ahmed, Qadeer & Chunodkar, Apurva, 2023. "Comprehensive energy footprint benchmarking of commercial electrified powertrains," Applied Energy, Elsevier, vol. 345(C).
    • Handle: RePEc:eee:appene:v:345:y:2023:i:c:s0306261923006633
    DOI: 10.1016/j.apenergy.2023.121299
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    References listed on IDEAS

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    1. Eckert, Jony Javorski & Silva, Fabrício L. & da Silva, Samuel Filgueira & Bueno, André Valente & de Oliveira, Mona Lisa Moura & Silva, Ludmila C.A., 2022. "Optimal design and power management control of hybrid biofuel–electric powertrain," Applied Energy, Elsevier, vol. 325(C).
    2. Tran, Dai-Duong & Vafaeipour, Majid & El Baghdadi, Mohamed & Barrero, Ricardo & Van Mierlo, Joeri & Hegazy, Omar, 2020. "Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    3. Tobias Nüesch & Philipp Elbert & Michael Flankl & Christopher Onder & Lino Guzzella, 2014. "Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs," Energies, MDPI, vol. 7(2), pages 1-23, February.
    4. M. Sabri, M.F. & Danapalasingam, K.A. & Rahmat, M.F., 2016. "A review on hybrid electric vehicles architecture and energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1433-1442.
    5. Wei, Shouyang & Zou, Yuan & Sun, Fengchun & Christopher, Onder, 2017. "A pseudospectral method for solving optimal control problem of a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 194(C), pages 588-595.
    6. Kim, Youngki & Figueroa-Santos, Miriam & Prakash, Niket & Baek, Stanley & Siegel, Jason B. & Rizzo, Denise M., 2020. "Co-optimization of speed trajectory and power management for a fuel-cell/battery electric vehicle," Applied Energy, Elsevier, vol. 260(C).
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