Development of Optimal Control Strategy for a Plug-In Series Hybrid Electric Vehicle With an On-Board Engine-Generator System for Overall Fuel Economy Improvement and Reduction in Tail-Pipe Emissions

2017 ◽  
Author(s):  
Aman V. Kalia ◽  
Brian C. Fabien
Keyword(s):  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Control Algorithms ◽  
Optimal Control Strategy ◽  
Generator System ◽  
Tail Pipe ◽  
Series Hybrid Electric Vehicle ◽  
In Series ◽  
Fuel Economy Improvement ◽  
Hybrid Electric

This research study focuses on determining optimal points of operation for the engine-generator system and regenerative braking at the wheels in a plug-in series hybrid electric Chevrolet Camaro. The goal is to improve overall fuel economy of the vehicle as well as reducing overall tail-pipe emissions. An abstract mathematical model of the series hybrid electric Chevrolet Camaro is being used to simulate the overall energy consumption of the vehicle. Previously tested and published control algorithms and strategies are studied, discussed and a viable scheme is chosen for optimization. The results from the optimal strategy considered are compared against the unoptimized results. An improvement of ∼ 8.9% in fuel economy and ∼ 8.2% reduction in tail-pipe emissions is estimated.

Match and Optimization of Series Hybrid Bus Powertrain Parameters

2011 ◽  
Vol 121-126 ◽  
pp. 2710-2714
Author(s):  
Ling Cai ◽  
Xin Zhang
Keyword(s):  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Simulation Platform ◽  
Optimal Method ◽  
Orthogonal Method ◽  
Series Hybrid Electric Vehicle ◽  
Hybrid Bus ◽  
Promising Solution ◽  
Hybrid Electric

With the requirements for reducing emissions and improving fuel economy, it has been recognized that the electric, hybrid electric powered drive train technologies are the most promising solution to the problem of land transportation in the future. In this paper, the parameters of series hybrid electric vehicle (SHEV), including engine-motor, battery and transmission, are calculated and matched. Advisor software is chosen as the simulation platform, and the major four parameters are optimized in orthogonal method. The results show that the optimal method and the parameters can improve the fuel economy greatly.

Fuel economy and NOx emission potential investigation and trade-off of a hybrid electric vehicle based on dynamic programming

2008 ◽  
Vol 222 (10) ◽  
pp. 1851-1864 ◽  
Author(s):  
G-Q Ao ◽  
J-X Qiang ◽  
H Zhong ◽  
X-J Mao ◽  
L Yang ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Cost Function ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Pollutant Emissions ◽  
Power Requirement ◽  
Trade Off ◽  
Fuel Economy Improvement ◽  
Hybrid Electric ◽  
Potential Improvement

Hybrid electric vehicles (HEVs) combined with more than one power source offer additional flexibility to improve the fuel economy and to reduce pollutant emissions. The dynamic-programming-based supervisory controller (DPSC) presented here investigates the fuel economy improvement and emissions reduction potential and demonstrates the trade-off between fuel economy and the emission of nitrogen oxides (NO x) for a state-of-charge-sustaining parallel HEV. A weighted cost function consisting of fuel economy and emissions is proposed in this paper. Any possible engine-motor power pairs meeting with the power requirement is considered to minimize the weighted cost function over the given driving cycles through this dynamic program algorithm. The fuel-economy-only case, the NO x-only case, and the fuel-NO x case have been achieved by adjusting specific weighting factors, which demonstrates the flexibility and advantages of the DPSC. Compared with operating the engine in the NO x-only case, there is 17.4 per cent potential improvement in the fuel-economy-only case. The fuel-NO x case yields a 15.2 per cent reduction in NO x emission only at the cost of 5.5 per cent increase in fuel consumption compared with the fuel-economy-only case.

Fuel Economy Improvement Analysis of Hybrid Electric Vehicle

2019 ◽  
Vol 20 (3) ◽  
pp. 531-537 ◽  
Author(s):  
InChun Chung ◽  
Hyehyun Kang ◽  
Jinil Park ◽  
Jonghwa Lee
Keyword(s):  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Fuel Economy Improvement ◽  
Hybrid Electric
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