Comparative Analysis of Hybrid Vehicle Energy Management Strategies with Optimisation of Fuel Economy and Battery Life

Energy ◽  
2021 ◽  
pp. 120604
Author(s):  
Shradhdha Sarvaiya ◽  
Sachin Ganesh ◽  
Bin Xu
Keyword(s):  
Comparative Analysis ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategies ◽  
Hybrid Vehicle ◽  
Battery Life

Real-World Robustness for Hybrid Vehicle Optimal Energy Management Strategies Incorporating Drivability Metrics

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Daniel F. Opila ◽  
Xiaoyong Wang ◽  
Ryan McGee ◽  
R. Brent Gillespie ◽  
Jeffrey A. Cook ◽  
...  
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Real World ◽  
Power Flow ◽  
Design Method ◽  
Management Strategies ◽  
Hybrid Vehicle ◽  
Stochastic Dynamic ◽  
Real World Data ◽  
Industrial Controller

Hybrid vehicle fuel economy and drive quality are coupled through the “energy management” controller that regulates power flow among the various energy sources and sinks. This paper studies energy management controllers designed using shortest path stochastic dynamic programming (SP-SDP), a stochastic optimal control design method which can respect constraints on drivetrain activity while minimizing fuel consumption for an assumed distribution of driver power demand. The performance of SP-SDP controllers is evaluated through simulation on large numbers of real-world drive cycles and compared to a baseline industrial controller provided by a major auto manufacturer. On real-world driving data, the SP-SDP-based controllers yield 10% better fuel economy than the baseline industrial controller, for the same engine and gear activity. The SP-SDP controllers are further evaluated for robustness to the drive cycle statistics used in their design. Simplified drivability metrics introduced in previous work are validated on large real-world data sets.

scholarly journals Energy Management Strategy for Fuel Cell and Battery Hybrid Vehicle Based on Fuzzy Logic

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 882
Author(s):  
Dongxu Li ◽  
Bing Xu ◽  
Jie Tian ◽  
Zheshu Ma
Keyword(s):  
Fuzzy Logic ◽  
Fuel Cell ◽  
Energy Management ◽  
Fuel Economy ◽  
Cell Hybrid ◽  
Management Strategy ◽  
Hybrid Vehicle ◽  
Hybrid Vehicles ◽  
Energy Management Strategy ◽  
Fuel Cell Hybrid

In order to improve fuel economy and enhance operating efficiency of fuel cell hybrid vehicles (FCHVs), fuzzy logic control (FLC) strategies are available and suggested for adoption. In this paper, the powertrain of a fuel cell hybrid vehicle is designed and the parameters of the motor, battery, and fuel cell are calculated. The FLC strategy and the power following control (PFC) strategy are designed for the studied FCHV. A secondary development for Advanced Vehicle Simulator (ADVISOR) is implemented based on the standard driving cycles, and a Chinese typical city driving cycle is imported. Simulation results demonstrate that the proposed FLC strategy is more valid and reasonable than the traditional PFC strategy. The proposed FLC strategy affects the vehicle characteristics significantly and contributes to better performance in four aspects: fuel economy, efficiency of battery and fuel cell system, battery state of charge (SOC), and battery life. Hence, the FLC strategy is more suitable for the energy management strategy for fuel cell and battery hybrid vehicles.

Optimal Equivalent Consumption Minimization Strategy for Plug-In Hybrid Electric Vehicle with Improved Genetic Algorithm

2020 ◽  
Vol 9 (2) ◽  
pp. 143-154
Author(s):  
Changyin Wei ◽  
◽  
Yong Chen ◽  
Xiuxiu Sun ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Management ◽  
Fuel Economy ◽  
Battery Life ◽  
Improved Genetic Algorithm ◽  
Life Index ◽  
Battery Capacity ◽  
Equivalent Factor ◽  
Equivalent Consumption Minimization Strategy

The equivalent consumption minimization strategy (ECMS) is a promising energy management approach to low-fuel economy with the outstanding features of high efficiency. In this article, an optimal ECMS by Improved Genetic Algorithm (IGA) is proposed. To this end, we improved the genetic algorithm (GA) from the coding method, initialization mode, and cross and mutation process. And based on the comprehensive energy consumption and Pontryagin’s minimum principle, the equivalent factor was derived. The IGA was used to optimize the equivalent factor. To evaluate the performance of the proposed energy management strategy (EMS), the average efficiency of the engine and the motor was analyzed in an urban area, high-speed area, and the whole area. The comprehensive fuel consumption was used as the energy consumption index, and the battery capacity loss under the transient conditions was amplified to 10 years as the evaluation battery life index. The simulation results show that under the New European Driving Cycle (NEDC), the proposed strategy improves the fuel economy and battery life index by 14.64% and 36.76%, respectively, compared with the rule-based EMS.

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