Power Flow Control in Hybrid Electric Vehicles

2011 ◽  
Author(s):  
Guillermo Becerra ◽  
Jose´ Luis Mendoza-Soto ◽  
Luis Alvarez-Icaza
Keyword(s):  
Flow Control ◽  
Fuel Consumption ◽  
Electric Vehicles ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Optimization Problems ◽  
Combustion Engine ◽  
Computational Cost ◽  
Power Flow Control ◽  
Hybrid Electric

In this paper a new strategy for controlling the power flow in hybrid electric vehicles is described. The strategy focuses in the planetary gear system where kinematic and dynamic constraints must be satisfied. The aim is to satisfy driver demands and to reduce fuel consumption. The resultant power flow control is continuous and uses the internal combustion engine with the maximum possible efficiency. The strategy is not optimal, although it is inspired by the solution to most optimization problems. The main advantages are that the computational cost is low, when compared to optimization based approaches, and that it is easy to tune. The strategy is tested with simulations using a mathematical model of a power train of a hybrid diesel-electric bus subjected to the power demands of representative urban area driving cycles. Simulation results indicate that the strategy achieves small speed tracking errors and attains good fuel consumption reduction levels.

scholarly journals An Agent based Power Flow Control for Hybrid Electric Vehicles

2004 ◽  
Vol 37 (22) ◽  
pp. 481-488
Author(s):  
Lucio Ippolito ◽  
Vincenzo Loia ◽  
Pierluigi Siano
Keyword(s):  
Flow Control ◽  
Electric Vehicles ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Power Flow Control ◽  
Agent Based ◽  
Hybrid Electric

Power flow control strategies in parallel hybrid electric vehicles

2016 ◽  
Vol 230 (14) ◽  
pp. 1925-1941 ◽  
Author(s):  
Guillermo Becerra ◽  
Luis Alvarez-Icaza ◽  
Alfonso Pantoja-Vázquez
Keyword(s):  
Flow Control ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Dynamic Models ◽  
Combustion Engine ◽  
Control Strategies ◽  
Planetary Gear ◽  
Driving Cycle ◽  
Power Flow Control ◽  
Planetary Gear System

Two control strategies for power flow control in hybrid electric vehicles (HEVs) with parallel configuration and a planetary gear system as a power coupling device between the internal combustion engine and the electric machine are proposed in this paper. The aim of both strategies is to determine, for a given driving cycle, an appropriate mixture of the power provided by the two engines. Performance is measured not only in terms of fuel consumption; driving cycle tracking and preservation of energy in the bank of batteries are also considered. The first strategy, named the PGS strategy as it is designed around the planetary gear system, is heuristic, inspired by bang–bang optimal control formulations and has low computational load, while the second is an optimal one derived from Pontryagin’s minimum principle (PMP). It is shown that, under appropriate choice of the weighting parameters in the Hamiltonian of the PMP, both strategies give very similar results and, therefore, that the PGS strategy corresponds to a feasible solution to an optimization problem. Both strategies can be implemented in real time, however, the PGS strategy is easier to tune. Tuning of the strategies’ parameters is independent of the driving cycle. The power flow control laws are continuous and enforce the use of the internal combustion engine with the maximum possible efficiency. The strategies are tested with simulations of a power train of a hybrid diesel–electric bus subjected to the demands of four representative urban area driving cycles. Although optimization solutions are based on simplified dynamic models, simulation results are verified with more detailed dynamic models of the HEV main subsystems. This allows us to evaluate the accuracy of the results and to verify the hypothesis established in the optimization formulation. Simulation results indicate that both strategies attain good fuel consumption reduction levels.

scholarly journals Model-Based Optimization of a Plug-In Hybrid Electric Powertrain with Multimode Transmission

2018 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
Stefan Geng ◽  
Andreas Meier ◽  
Thomas Schulte
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Electric Motor ◽  
Energy Savings ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Optimal Number ◽  
Model Based ◽  
Hybrid Electric ◽  
Motor Operation

Plug-in hybrid electric vehicles are developed in order to reduce the fuel consumption and the emission of carbon dioxide. Besides the series, parallel and power split configurations are commonly used for conventional hybrid electric vehicles, and multimode transmissions are used for plug-in hybrid electric vehicles, which are able to switch between different modes like parallel or series operation of the combustion engine and electric motor. Several concepts have already been discussed and presented. These concepts comprise novel structures and multi-speed operation for the combustion engine and the electric motor, respectively. For improving the fuel and energy consumption, model-based optimizations of multimode transmissions are performed. In the first step of the optimization, the optimal number of gears and transmission ratios, as well as the corresponding fuel and energy savings, are estimated. Based on these results, a new multimode transmission concept with two-speed transmissions for the combustion engine and the electric motor has been developed. The knowledge of the concrete concept enables the further optimizations of the transmission ratios and the transmission control. In order to prove the benefit of the new and optimized transmission concept, powertrain simulations have been carried out. The new powertrain concept is compared to a powertrain concept with single-speed transmissions for the internal combustion engine (ICE) and electric motor operation. The new transmission concept enables a significant improvement of the fuel consumption.

System Integration for the Environmental Friendly Electric Vehicle

2014 ◽  
Vol 709 ◽  
pp. 300-303
Author(s):  
Kuang Shine Yang ◽  
Chih Ming Chang
Keyword(s):  
Flow Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
System Integration ◽  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Combustion Engine ◽  
Maximum Speed ◽  
Power Flow Control ◽  
Control Approach

This paper introduced a new power flow control strategy for a variable speed engine-generator based range-extended electric vehicle. The specific fuel consumption map of the internal combustion engine (ICE) has been obtained by off-line experiments to achieve optimal fuel efficiency. Finally, a typical range-extended electric vehicle is modeled and investigated such as acceleration traversing ramp, maximum speed, fuel consumption and emission are performed on the dynamic model of a range-extended electric vehicle. The energy consumption and cost were compared to tradition range-extended electric vehicle. Computer simulation results obtained, confirm the validity and performance of the proposed power flow control approach using for series hybrid electric vehicle.

scholarly journals Optimal Energy Management for Hybrid Electric Vehicles Based on Dynamic Programming and Receding Horizon

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3502
Author(s):  
Pierpaolo Polverino ◽  
Ivan Arsie ◽  
Cesare Pianese
Keyword(s):  
Dynamic Programming ◽  
Fuel Consumption ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Driver Assistance Systems ◽  
Receding Horizon ◽  
Simulated Environment ◽  
Hybrid Electric

Fuel consumption and emissions in parallel hybrid electric vehicles (HEVs) are directly linked to the way the load request to the wheels is managed between the internal combustion engine and the electric motor powered by the battery. A significant reduction in both consumption and emissions can be achieved by optimally controlling the power split on an entire driving mission (full horizon—FH). However, the entire driving path is often not predictable in real applications, hindering the fulfillment of the advantages gained through such an approach. An improvement can be achieved by exploiting more information available onboard, such as those derived from Advanced Driver Assistance Systems (ADAS) and vehicle connectivity (V2X). With this aim, the present work presents the design and verification, in a simulated environment, of an optimized controller for HEVs energy management, based on dynamic programming (DP) and receding horizon (RH) approaches. The control algorithm entails the partial knowledge of the driving mission, and its performance is assessed by evaluating fuel consumption related to a Worldwide harmonized Light vehicles Test Cycle (WLTC) under different control features (i.e., horizon length and update distance). The obtained results show a fuel consumption reduction comparable to that of the FH, with maximum drift from optimal consumption of less than 10%.

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