Multi-objective real-time optimization energy management strategy for plug-in hybrid electric vehicle

Abstract

Plug-in hybrid electric vehicle provides remarkable results for emission reduction and fuel improvement in the current driving cycles. With the appropriate energy management strategy, the torque can be split by switching of multiple operation modes to improve fuel economy. However, in the process, not only the noticeable jerk or torque fluctuation, which may result in vibration of the drivetrain and unpleasant driving sensation, but also the frequent motor-start-engine process would be triggered, which is accompanied by extra fuel consumption and abrasion of the clutch. Therefore, high attention should be paid to reduce the excess operating times of the motor-start-engine process and take advantage of multiple operation modes to improve fuel economy in plug-in hybrid electric vehicle. To solve this problem, a multi-objective real-time optimization energy management strategy is proposed. First, the motor-start-engine dynamic model of 2-degree-of-freedom is established. Then, the motor-start-engine process is analyzed based on a large number of real-world data, and the cost of the motor-start-engine process is quantified for optimization. What’s more, the optimal torque distribution is realized through the powertrain system. Finally, the proposed strategy is verified by the simulation and experiment platform. Results show that the proposed strategy can greatly improve fuel economy, thereby reducing the excess operating times of the motor-start-engine process.

Design of an Aftermarket Hybridization Kit: Reducing Costs and Emissions Considering a Local Driving Cycle

“…Thus, the throttle pedal signal is acquired and the PMC splits the requested traction torque T eng according to the P E factor (defined in the optimization problem). The engine torque T eng and torque of the electric motors T el are defined by Equations (6) and (7) respectively, according to the engine inertia I e (kgm 2 ); gearbox and differential gear ratios N t and N d ; inertia I t (kgm 2 ) and I d (kgm 2 ); the frontal and real wheels inertia I w f (kgm 2 ) and I wr (kgm 2 ); and the overall powertrain efficiency η td .…”

“…The relevance of the plug-in electric vehicles (PHEVs) in the current engineering is reflected by the recent scientific activities. Du et al [7] optimized a plug-in hybrid bus to avoid excessive changes of operation modes, reducing the number of engine startups, the clutch abrasion and the jerk. Golpîra and Khan [8] pointed that the increasing use of PHEVs is an important issue to be taken into account in domestic energy power management, while Li et al [9,10] investigated the advantages for the power distribution systems due to the optimum coordination of the PHEVs charging times.…”

Efficiency improvement of a novel dual motor powertrain for plug-in hybrid electric buses

“…For reasonable comparisons, the two configurations use a same battery pack that consists of 100 lithium-ion cells connected in series. Each cell has the capacity of 180 A h, the nominal voltage of 3.8 V and the nominal internal resistance of 0.11.10 –2 Ω. Therefore, the parameters of the battery pack are presented as in Table 2.…”

“…For the urban commute, plug-in hybrid electric buses (HEBs) are widely considered as the most effective solution. 1,2 The engine of plug-in HEBs can avoid working in lower efficiency regions with motor support. In addition, the ability to recharge a battery from external sources reduces the heavy reliance on fossil fuels.…”

Socio-technical smart grid optimization via decentralized charge control of electric vehicles

“…Related work on charging control of electric vehicles is classified in three categories: (i) Non-coordinated optimization of battery utilization to improve environmental factors and the individual driving profile of a vehicle [13,14] as well as the multi-objective optimization of plug-in hybrid electric vehicles [15,16,17], e.g. fuel economy and motor start engine.…”