Effects of Drive-Train Hybridization on Fuel Economy and Dynamic Performance of a Series Hybrid Electric Transit Bus

2008 ◽  
Author(s):  
Samaneh Haddadi ◽  
Vahid Esfahanian ◽  
Hassan Nehzati ◽  
Farhad Sangtarash ◽  
Arash Akhgari
Keyword(s):  
Fuel Economy ◽  
Dynamic Performance ◽  
Drive Train ◽  
Hybrid Electric ◽  
Transit Bus

Matching and Optimization for Powertrain System of Parallel Hybrid Electric Vehicle

2013 ◽  
Vol 341-342 ◽  
pp. 423-431
Author(s):  
Jian Ping Gao ◽  
Yue Hui Wei ◽  
Zhen Nan Liu ◽  
Hong Bing Qiao
Keyword(s):  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Dynamic Performance ◽  
Hybrid Powertrain ◽  
Parallel Hybrid Electric Vehicle ◽  
Powertrain System ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Avl Cruise

The parameters matching of the hybrid powertrain system of the hybrid electric vehicle has a directly impact on the performance of the vehicle dynamic and the fuel economy. The preliminary match of the powertrain system base on analysis of Driving Cycle is done, then the software of AVL-Cruise and Matlab are integrated with Isight to optimize parameters of match, by using the Multi-Island GA and NLPQL to establish the combinatorial optimization algorithm. The results show that the fuel economy have been improved by 10.92% without sacrificing the dynamic performance and under the premise of ensuring the limits of the state of charge of battery.

Optimization of Hybrid Electric Bus Control Strategy with Hybrid Optimization Algorithm

2013 ◽  
Vol 341-342 ◽  
pp. 924-930
Author(s):  
Jian Ping Gao ◽  
Zhen Nan Liu ◽  
Zhi Jun Guo ◽  
Yue Hui Wei
Keyword(s):  
Optimization Algorithm ◽  
Fuel Economy ◽  
Control Strategy ◽  
Dynamic Performance ◽  
Hybrid Optimization ◽  
Hybrid Electric Bus ◽  
Hybrid Optimization Algorithm ◽  
Electric Bus ◽  
Hybrid Electric ◽  
Strategy Parameters

control strategy is one of the most decisive techniques in Hybrid Electric Bus (HEB) and directly influences the dynamic performance and fuel economy. For achieving the best fuel economy and keeping the battery for a long time, First, power analytic control strategy was built; then, the hybrid optimization algorithm (HOA) based on Multi-island genetic Algorithm (MIGA) and NLPQL was built by ISIGHT software. HOA is adopted in control strategy parameters of HEB optimization. The results show that the best result can be obtained in few iterative times by HOA, the calculation time was reduce by 12 hours, the fuel economy was improved by 12% and find the rules between control strategy parameters and fuel economy the balance of the battery state of charge (SOC).

A unified quantitative analysis of fuel economy for hybrid electric vehicles based on energy flow

2021 ◽  
Vol 292 ◽  
pp. 126040
Author(s):  
Xiaohua Zeng ◽  
Qifeng Qian ◽  
Hongxu Chen ◽  
Dafeng Song ◽  
Guanghan Li
Keyword(s):  
Quantitative Analysis ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Energy Flow ◽  
Hybrid Electric Vehicles ◽  
Hybrid Electric

scholarly journals A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3147
Author(s):  
Kiyoung Kim ◽  
Namdoo Kim ◽  
Jongryeol Jeong ◽  
Sunghwan Min ◽  
Horim Yang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Hybrid Electric Vehicle ◽  
New Technologies ◽  
New Technology ◽  
Dynamic Performance ◽  
Minimum Principle ◽  
Component Sizing ◽  
Hybrid Electric

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

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.

Research on Torque Distribution Strategy for ISG Hybrid Electric Cars

2012 ◽  
Vol 546-547 ◽  
pp. 212-217
Author(s):  
Xu Dong Wang ◽  
Hai Xing Zhang ◽  
Shu Cai Yang ◽  
Yong Qin Zhou ◽  
Jin Fa Liu
Keyword(s):  
Hybrid System ◽  
Fuel Economy ◽  
Test Model ◽  
Torque Distribution ◽  
Electric Cars ◽  
Distribution Strategy ◽  
Hybrid Car ◽  
Total Vehicle ◽  
Hybrid Electric ◽  
Minimum Work

Based on the configuration and working state analysis of the ISG hybrid electric cars, the torque distribution strategy of a hybrid system is designed to delineate the maximum and minimum work torque curves of the engine, achieve optimization of engine’s range so as to make sure the target torque of the engine and ISG motor, and finally through the calibrated driving characteristics MAP and battery SOC state to achieve the calculation of total vehicle torque demand. Taking the Hafei Saibao ISG hybrid car as a test model, the test of fuel economy and emissions carried out under specific conditions showed that using the torque distribution strategy has increased by 12.8 % of the ISG hybrid car fuel economy and improved emissions performance to some extent compared to the traditional Hafei Saibao cars.

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