Abstract
This paper reviews the latest studies of hybrid electric vehicles (HEVs) on modelling, controls, and energy management. HEV dynamics, formulas, calculations, and schemes of vehicle parts, such as battery, converter, electric motor, generator, and HEV Simulink models, are presented. Moreover, simulations of the propulsion operation, regenerative braking system, and vehicle dynamics are conducted. A comprehensive HEV model is built that is simulated on different driving cycles of Federal Test Procedure 75 (FTP75), New York City Cycle (NYCC), Highway Fuel Economy Test (HWFET), and Extra Urban Driving Cycle (EUDC). Data achieved from these simulations were analysed and tested with several fuel regression models to determine the best fuel regression estimation for HEV fuel consumption on the basis of their weights and tire radiuses. The best fuel regression equation is obtained with a determination coefficient R-squared greater than 99%. Lastly, the optimal model and other HEVs models are simulated on different driving cycles to prove that the fuel consumption of our best-fit regression model is the best.
Highlights
Hybrid electric vehicles (HEVs) have been increasingly popular since the global commitment to restrain the use of fossil fuels and to limit CO2 emissions
At a very high speed or very high load, the vehicle is run by both EM2 and internal combustion engines (ICEs)
This study reviewed the latest developments of fuel consumption economy for HEV
Summary
Hybrid electric vehicles (HEVs) have been increasingly popular since the global commitment to restrain the use of fossil fuels and to limit CO2 emissions. Another systematic review of the recent technologies, control methods, and energy optimization managers for HEVs was presented in [2]. In reviewing recent HEV energy management and optimal control, the authors in [3]. In [13], the authors studied the modelling and fuel management of powertrain split on HEVs. Six operation modes of the vehicles were discussed for the impact of different fuel management strategies on energy and energy efficiency analysis were presented in [14]. This study investigates the feasibility of optimising control for different driving patterns, so that the vehicle can maintain a high level of optimality regardless of the driving pattern Another control strategy for clutch engagement during mode changing for HEVs was presented in [18]. The authors in [20] conducted research on the multiphase mixed integer nonlinear optimal control of HEVs for a minimal fuel energy management strategy. The latest mathematical formulations are referred to in [36–39]
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