Analytical Approach for the Power Management of Blended-Mode Plug-In Hybrid Electric Vehicles

Zhang, Menyang; Yang, Yan; Mi, Chris

doi:10.1109/tvt.2012.2187318

Cited by 84 publications

(37 citation statements)

References 27 publications

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“…The HEVs performance is tightly dependent on the power management strategies used to control the power flow between the different subsystems [4]. The essence of HEV PMS is determining when and how to use the ICE to fulfill the request output torque (or power) while maintaining battery within a range and minimizing frictional braking [48].…”

Section: Pms -Power Management Systemmentioning

confidence: 99%

An Influence Study of Parallel Hybrid Vehicle Propulsion System Configurations

Eckert

Corrêa

Santiciolli

et al. 2015

Anais Do XXIII Simpósio Internacional De Engenharia Automotiva

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The hybrid electric vehicle (HEV) became an alternative to reduce the fuel consumption. The HEV parallel configuration consists of two separated drive systems, such as the engine/powertrain system and an extra electric motors (EMs) system. The addition of an extra electrical power changes the engine operation point and consequently the fuel consumption. However, there are many ways to introduce this electrical power source as a secondary drive system. In this paper, two parallel HEV configurations are studied in a condition where the conventional engine/powertrain system, coupled to the vehicle front wheels, is the main power source and two different configurations of EMs drive system, coupled to the rear wheels, are auxiliary power sources. The first one consists of two in-wheel motors coupled directly to the vehicle rear wheels and the other one is an EM coupled to a differential system similar to the existent in the conventional vehicle powertrain. The aim of this paper is to simulate and compare the HEV behavior with the conventional vehicle behavior, both of them running in the Brazilian urban drive cycle NBR6601, evaluating differences in performance, fuel consumption and battery discharging when applicable. INTRODUTIONThe increasing number of cars may be causing serious effects to the environment and to humans, such as pollution, global warming, depletion of oil reserves, among others The hybrid vehicles use different power sources with various powertrain configurations, including the ICE, electric motors (EMs), electric generators and battery packs [6]. In this paper are studied the hybrid electric vehicles (HEVs) that are one of the solutions proposed to minimize problems associated with the energy crisis and global warming [3]. These vehicles consume less gasoline and emit less pollution than conventional vehicles without decreasing

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Section: Pms -Power Management Systemmentioning

confidence: 99%

An Influence Study of Parallel Hybrid Vehicle Propulsion System Configurations

Eckert

Corrêa

Santiciolli

et al. 2015

Anais Do XXIII Simpósio Internacional De Engenharia Automotiva

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“…Since there exists some uncertainty for driving cycles, driver's habits, and weather conditions that can influence the energy distribution in the PHEV, from this point, it can be said that the energy management is a stochastic optimization problem. Actually, popular control candidates can be divided into four types: (1) rule based control method [3][4][5]; (2) intelligent control methods, including artificial neural network (ANN) [6,7], fuzzy logic [8,9], model predictive control (MPC) [10,11], and machine learning algorithm [12,13]; (3) analytic methods [14,15]; and (4) optimization based control method, including deterministic dynamic programming (DP) [1,[16][17][18][19]], Pontryagin's Minimum Principle (PMP) [20,21], quadratic programming (QP) [22,23], and convex optimization [24][25][26]. These methods' purpose can include improving the fuel economy, reducing emissions [27,28], prolonging cycling life of the battery pack [2,29], minimizing the operation cost [30], etc.…”

Section: Introductionmentioning

confidence: 99%

Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming

et al. 2018

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This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power at different vehicle speed and driveline power demand. The engine-on power threshold is estimated by the simulated annealing (SA) algorithm, and the battery power command is achieved by convex optimization with target of improving fuel economy, compared with the dynamic programming (DP) based method and the charging depleting-charging sustaining (CD/CS) method. In addition, the proposed control methods are discussed at different initial battery state of charge (SOC) values to extend the application. Simulation results validate that the proposed strategy based on convex optimization can save the fuel consumption and reduce the computation burden obviously.

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“…Zhang et al have proposed a real-time control strategy that selects the most power efficient mode of a multimode HEV powertrain to achieve near-optimal fuel-economy [28]. A similar method is described in Shabbir and Evangelous work [29], Other control strategies on multi-mode HEVs are found in the work of Zhang et al [30], Borhan et al [31], Ahn and Papalambros [32], Katrašnik [33], and Lin et al [34], among others.…”

Section: Introductionmentioning

confidence: 99%