Real-time Predictive Energy Management of Hybrid Electric Heavy Vehicles by Sequential Programming
Artikel i vetenskaplig tidskrift, 2021

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 determines the 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 with a length of 5-20 km. 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 the development of a sequential linear program for predictive energy management that is faster and simpler than sequential quadratic programming in tested solvers and gives trajectories that are very close to the best trajectories found by nonlinear programming. The performance of the method is also compared to two different sequential quadratic programs.

optimal control

sequential linear programming

predictive energy management strategy

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

Volvo Group

Leo Laine

Volvo Group

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 70 5 4113-4128

Distribuerad framdrivning mellan enheter i en lång fordonskombination

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

Energimyndigheten (41037-1), 2015-10-01 -- 2019-12-31.

Användning av i-dolly för lokal distribution av container trailers till logistikterminaler från en torr-hamn

VINNOVA (2017-03036), 2017-09-01 -- 2020-08-31.

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

DOI

10.1109/TVT.2021.3069414

Mer information

Senast uppdaterat

2021-06-16