Hardware-in-the-loop exploration of energy versus emissions trade-off in eco-following scenarios for connected automated vehicles

Huang, Chunan; Salehi, Rasoul; Stefanopoulou, Anna G.; Ersal, Tulga

doi:10.1177/14680874221098212

Cited by 2 publications

(3 citation statements)

References 36 publications

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“…Our focus in this paper is to optimize emissions considering the engine and ATS control versus the previous work which was on the vehicle speed optimization. 14 To this end, this paper presents a real-time model based predictive control design for a diesel engine which would control both the engine airpath and the aftertreatment states to address the fuel economy -NO X emission tradeoff. The performance of this controller was evaluated in real-time in a HIL setup.…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

Duraiarasan

Salehi

Mahesh

et al. 2023

International Journal of Engine Research

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For heavy-duty diesel engines, NOX emissions reduction is strongly constrained by fuel efficiency. This paper presents a hierarchical model predictive controller (H-MPC) for coordinated control of tailpipe NOX emissions and fuel consumption. The H-MPC uses the separation of slow and fast dynamics that exist in the engine and its aftertreatment system. The controller is synthesized with an architecture in which a high-level MPC uses a longer prediction horizon compared to the low-level predictive controller which tracks the high-level controller command and manages the thermal dynamics of the aftertreatment system. Engine load preview enables the high-level controller to estimate the desired catalyst temperature ahead of time and addresses the selective catalytic reduction (SCR) slow thermal dynamics. Calculated by the high-level controller, the intake manifold pressure, and the start of injection (SOI) crank angle is used as reference trajectories in the low-level controller that regulates fast dynamical behaviors such as engine out NOX emissions. Hardware-in-the-loop (HIL) validation of this integrated H-MPC on a rapid prototype controller shows that when the SCR catalyst temperature is above light-off temperature (warmed-up condition), the engine operation is shifted to operate with the best fuel economy since the warmed-up SCR can efficiently reduce the engine-out NOX emissions. Results indicate that up to 0.8% benefit in cycle averaged BSFC along with a 13% reduction in tailpipe NOX compared to a stock engine calibration can be achieved with the coordinated engine and aftertreatment system through H-MPC.

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Section: Introductionmentioning

confidence: 99%

“…Our focus in this paper is to optimize emissions considering the engine and ATS control versus the previous work which was on the vehicle speed optimization. 14…”

Section: Introductionmentioning

confidence: 99%

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

Duraiarasan

Salehi

Mahesh

et al. 2023

International Journal of Engine Research

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“…However, the benefits of look-ahead information were not reported. Similarly, in [28] where energy-emission tradeoff is studied under eco-following scenarios for connected automated vehicles, the difference in using look-ahead information is not analyzed. Velmurugan et al [29] used a 60-s "look-ahead" for aftertreatment control to calculate the optimal engine-out NOx set points to minimize fuel and urea consumption while ensuring legislative-compliant tailpipe emissions.…”

Section: Introductionmentioning

confidence: 99%

A Hierarchical Economic Model Predictive Controller That Exploits Look-Ahead Information of Roads to Boost Engine Performance

Liu

Dizqah

Herreros

et al. 2023

IEEE Trans. Contr. Syst. Technol.

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Sensors and communication capabilities of connected vehicles provide look-ahead information that can be exploited by vehicle controllers. This work demonstrates the benefits of look-ahead information combined with hierarchical economic model predictive control for the airpath management of compression ignition engines. This work exploits road information predicted with a 0.1-and 2-s horizon to simultaneously control fast and slow engine dynamics, respectively. It controls the variable nozzle turbocharger and dual-loop exhaust gas recirculation, at a 0.01-s rate, to simultaneously optimize NOx, soot, and fuel economy. Simulation studies and hardware-in-loop implementation on an ARM Cortex-A15 processor demonstrate improved NOx, soot, and torque tracking without compromising fuel economy, and a worst case computation time of 8.92 ms.

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Hardware-in-the-loop exploration of energy versus emissions trade-off in eco-following scenarios for connected automated vehicles

Cited by 2 publications

References 36 publications

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

A Hierarchical Economic Model Predictive Controller That Exploits Look-Ahead Information of Roads to Boost Engine Performance

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