Real-time Predictive Energy Management of Hybrid Electric Heavy Vehicles by Sequential Programming
Preprint, 2020

With the objective of reducing fuel consumption, this paper presents real-time predictive energy management of hybrid electric heavy vehicles. We propose an optimal control strategy that decides power split between different vehicle power sources and brakes. Based on the model predictive control (MPC) and sequential programming, the optimal trajectories of the vehicle velocity and battery state of charge are found for upcoming horizons of 5-20 km length. Then, acceleration and brake pedal positions together with the battery usage are regulated to follow the requested speed and state of charge that is verified using a vehicle plant model. The main contribution of this paper is developing a sequential linear program for predictive energy management that is faster compared to the sequential quadratic programming with a factor of 5 in tested solvers, giving very close trajectories to the best attained trajectories found by non-linear programming. The performance of the method is also compared to two different sequential quadratic programs.

predictive energy management strategy

sequential linear programming

optimal control

hybrid electric heavy vehicle

Författare

Toheed Ghandriz

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Bengt J H Jacobson

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Nikolce Murgovski

Chalmers, Elektroteknik, System- och reglerteknik, Mekatronik

Peter Nilsson

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Leo Laine

Chalmers, Mekanik och maritima vetenskaper

Distribuerad framdrivning mellan enheter i en lång fordonskombination

VINNOVA, 2015-10-01 -- 2019-12-31.

Energimyndigheten, 2015-10-01 -- 2019-12-31.

Ämneskategorier

Maskinteknik

Farkostteknik

Reglerteknik

Annan elektroteknik och elektronik

Drivkrafter

Hållbar utveckling

Innovation och entreprenörskap

Styrkeområden

Transport

Energi

Fundament

Grundläggande vetenskaper

Infrastruktur

ReVeRe (Research Vehicle Resource)

Lärande och undervisning

Pedagogiskt arbete

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Skapat

2020-09-01