E nergy Procedia  45  ( 2014 )  949 – 958
王大治图片1876-6102 © 2013 The Authors. Published by Elsevier Ltd. Op en a ccess u n d e r  CC BY-NC-ND license.
Selection and peer-review under responsibility of A TI NAZIONALE
doi: 10.pro.2014.01.100
橄榄树 刘彩星
ScienceDirect
Available online at www.sciencedirect
950L aura Tribioli et al. /  E nergy Procedia 45 ( 2014 )949 – 958
ηEfficiency
S oC State of Charge(State Variable)˙S oC State of Charge Time Derivative J Cost Function
u Control Vector
˙m Fuel massflow rate
H Hamiltonian Function(kg/s)
λCo-state(kg)
p Additive penalty function(kg) K Penalty weight value(kg) Subscripts and Superscripts
min Minimum Threshold
大碗宽面
max Maximum Threshold
wh Wheel L Load
veh Vehicle
des Desiredrussian girl
p Proportional
i Integral
eq Equivalent
c Coulombic華原朋美>少年说
oc Open Circuit
0Initial Value
f Final Value
f uel Fuel
∗Optimal Solution
ICE Internal Combustion Engine EM Electric Motor
BP Battery Pack
1.Introduction
Plug-in hybrid electric vehicles(PHEVs)are seen as a promising industry solution for reducing fuel consumption and pollutant emissions.Compared to hybrid electric vehicles(HEVs),PHEVs have the advantage of a longer battery life,and obviously of rechargeability from an external source.Fully recharging the battery allows for an extension of the acceptable operating range of the state of charge(SoC),thus reducing PHEVs fuel consumption with respect to HEVs,with the additional consequence of producing less CO2emissions,[1],[2].In total analogy with HEVs,the cumulative fuel economy of these vehicles depends in essence on the design of the powertrain components and on the choice of the architecture,[3],[4],but is particularly sensitive to the energy management control strategy implemented on-board,[5]and[6].
In PHEVs,the presence of a bigger battery which can be plugged to an external source to be restore
d to full charge introduces an additional degree of freedom beside conventional HEVs,since the larger allowable SoC range can be managed with different discharge strategies,[7].So far,the Charge Depleting/Charge Sustaining(CD/CS) operation is still the most implemented strategy,being rather unrelated to the driving mission.In this strategy,the battery is initially discharged operating the vehicle as a pure electric vehicle,until the SoC reaches thefinal desired value,which is then sustained until the end of the trip.Nonetheless,a blended battery discharge,which gradually reaches the desiredfinal SoC only at the end of the mission,results in the optimal energy management,and thus in the minimum fuel consumption and CO2emissions,[8].The battery SoC is hence a crucial element in the choice of the best algorithm for the energy management of such vehicles.In general,if a powertrain has the possibility of operating in different modes,the SoC should not only affect the power split,but also the supervisory controller decision on the mode of operation,[9].Several of the optimal control theory frameworks proposed for energy management of HEVs have been already applied to PHEVs,such as Dynamic Programming,[10],Equivalent Consumption Minimization Strategy,[11]or Pontryagin’s Minimum Principle(PMP),[12],[13],[14]aiming at the minimization of different cost functions.Nevertheless,the main issue in the realization of a blended strategy implementable online lies in the need of an a-priori knowledge of a number of information,such as the total distance to be traveled and the characteristics of the driving cycle(speed and grade profiles),in order to correctly cal
ibrate the optimization parameters and obtain the optimal battery SoC trajectory.On the other hand,a careful investigation on the powertrain behavior,when the optimal framework is applied,can help for the design of a satisfying heuristic control technique,which can lead to better results than the CD/CS strategy,being also independent on the driving mission.Similar studies have been already applied to HEVs,using for example the Dynamic Programming optimal algorithm as in[15].
In this paper a rule-based strategy is designed starting from the application of the PMP to a GM Chevrolet Malibu, which is originally driven only by an internal combustion engine(ICE).The aim of the study is to demonstrate the effectiveness of this rule-based strategy despite its naive implementation and low computational efforts.Also,the application to a re-engineered vehicle,aims at demonstrating the considerable fuel consumption reduction,while maintaining vehicle performance.In this application,the ICE has been coupled to an electric machine(EM)which
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