Christopher Aksland

  • Resume
  • aksland2@illinois.edu
  • Ph.D. Mechanical Engineering – University of Illinois (May 2022)
  • M.S. Mechanical Engineering – University of Illinois (Dec 2019)
  • B.S. Mechanical Engineering – University of Illinois (May 2017)
  • Research Interests: Control Systems, Power Systems
  •  

     
     
     

    Current Work

    Improved power management techniques are required to enhance the operating behavior of hybridized and electrified vehicles. However, the complex, multi-domain, and multi-timescale dynamics for this class of systems create challenges for real-time capable control design. Additionally, these vehicles have strict electrical and thermal operating constraints to maintain reliable operation. For example, battery state of charge, current, and temperature must remain within specific bounds to prevent premature degradation or thermal runaway. Chris’ latest work has focused on the application of model predictive control for the multi-timescale coordination of the electro-mechanical dynamics of a hybrid electric UAV powertrain. Simulated and hardware demonstrations of the predictive control designs showed improvements in the overall system performance, reliability, and efficiency in comparison to a well designed baseline controller (Fig. 1).

    Fig. 1 Comparison of performance, reliability, and efficiency metrics for the validated control designs presented in [5].

    Fig. 1 Comparison of performance, reliability, and efficiency metrics for the validated control designs presented in [5].

    Chris’ ongoing work considers the control design and validation for a full aircraft power system. A predictive hierarchical control framework that understands the electrical, mechanical, and thermal system coupling will be used to demonstrate enhancements in the aircraft operation.

    The validation of Chris’ control designs through testbed demonstrations are added value of the research. Chris currently works on the POETS Aerospace Vehicle testbed which is composed of a hybrid electric UAV powertrain (Fig. 2) and aircraft fuel thermal management system (Fig. 3).

    Fig. 2 Hybrid electric UAV powertrain testbed.

    Fig. 2 Hybrid electric UAV powertrain testbed.


    Fig. 3 Aircraft fuel thermal management system testbed.

    Fig. 3 Aircraft fuel thermal management system testbed.

     

    Publications

    Conference

    [1] Aksland, C.T., and Alleyne, A.G., “Experimental Model and Controller Validation for a Series Hybrid Unmanned Aerial Vehicle,” Proc. of the 2020 American Control Conference, July 2020. (accepted)

    [2] Aksland, C.T., Bixel, T.W., Raymond, L.C., Rottmayer, M.A., and Alleyne, A.G., “Graph-Based Electro-Mechanical Modeling of a Hybrid Unmanned Aerial Vehicle for Real-Time Applications,” Proc. of the 2019 American Control Conference, July 2019. [PDF]

    [3] Garrow, S.G., Aksland, C.T., Sharma, S. and Alleyne, A.G., “Integrated Modeling for Battery Electric Vehicle Transcritical Thermal Management System,” Proc. of the 2018 American Control Conference, June 2018. [PDF]

    [4] Aksland, C.T., Koeln, J.P., and Alleyne, A.G., “A Graph-Based Approach for Dynamic Compressor Modeling in Vapor Compression Systems,” Proc. of the ASME 2017 Dynamic Systems and Control Conference, October 2017. [PDF]

    Theses

    [5] Aksland, C.T., Modular Modeling and Control of a Hybrid Unmanned Aerial Vehicle’s Powertrain,” M.S. Thesis, Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, 2019. [PDF] (Coming Soon)