Optimal control of power split for a hybrid electric refuse vehicle

Serrao, Lorenzo; Rizzoni, Giorgio

doi:10.1109/acc.2008.4587204

Cited by 84 publications

(50 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Technically, the desired output trajectory is known a priori when the vehicle follows a certain drive cycle. Dynamic programming (DP) [3][4][5] and the analytical optimal control techniques [6][7][8] can then be used to obtain the theoretical optimal results. The results obtained through DP are unbeatable but, unfortunately, is an optimal input but not a control algorithm, and thus is not suitable for real-time implementation.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

et al. 2013

View full text Add to dashboard Cite

This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT). A control-oriented model of the powertrain and vehicle dynamics is built first. The energy management is formulated as a typical optimal control problem to trade off the fuel consumption and gear shifting frequency under admissible constraints. The Dynamic Programming (DP) and Pontryagin's Minimum Principle (PMP) are applied to obtain the optimal solutions. Tuning with the appropriate co-states, the PMP solution is found to be very close to that from DP. The solution for the gear shifting in PMP has an algebraic expression associated with the vehicular velocity and can be implemented more efficiently in the control algorithm. The computation time of PMP is significantly less than DP.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

et al. 2013

View full text Add to dashboard Cite

show abstract

“…Methods in use include deterministic [1]- [3] and stochastic dynamic programming [4], [5], Pontryagin's minimum principle [6], [7] and game theory [8]. The optimal control generally depends on knowledge about the probability distribution of factors such as power load over a specific driving cycle, and transferring the optimal solution to a feasible real-time strategy has proved an awkward process.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Control of Series HEVs Including Resistive Losses and Varying Engine Efficiency

Neuman¹,

Wahlberg²,

Folkesson³

2009

SAE Technical Paper Series

View full text Add to dashboard Cite

A model of a series HEV (Hybrid Electric Vehicle) including resistive losses in the energy storage and varying engine and generator efficiency is presented. The purpose is to study how system properties affect the optimal control of series HEVs. We show that there is an inherent trade-off in the control of such a system, based on the characteristics of the efficiency curve of the EGU (Engine and Generator Unit) together with the energy storage internal resistance, capacitance and energy level. The relation between these properties determines the optimal control of the EGU, and this is thus the mechanism behind all optimal control problems using a similar model setup. We illustrate our reasoning using deterministic dynamic programming where system properties are varied and the optimal control is studied.

show abstract

“…This approach assumes that the power train can be described with simple analytical functions. Thus, it is often a too simplified approach and it also requires the knowledge of the driving cycle to be applied (Anatone et al 2005, Serrao et al 2008). …”

Section: Approaches To the Supervisory Control Modelsmentioning

confidence: 99%

Intelligent Usage of Internal Combustion Engines in Hybrid Electric Vehicles

Donateo¹

2012

Internal Combustion Engines

View full text Add to dashboard Cite

Optimal control of power split for a hybrid electric refuse vehicle

Cited by 84 publications

References 11 publications

Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

Modelling and Control of Series HEVs Including Resistive Losses and Varying Engine Efficiency

Intelligent Usage of Internal Combustion Engines in Hybrid Electric Vehicles

Contact Info

Product

Resources

About