• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.591-600
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• 2015

The efficiency of a powertrain system of hybrid vehicle is highly dependent on the design and control of the hybrid powertrain system. In other words, the optimal design of the powertrain systems is coupled with optimal control of the powertrain system. Therefore, the solution of an optimal design problem for hybrid vehicles is computationally and timely very expensive. For example, dynamic programming, which is a recursive optimization method, is usually used to evaluate the best fuel economy of certain hybrid vehicle design, and, thus, the evaluation takes tens of minutes to several hours. This research aims to accelerate the speed of efficiency evaluation of hybrid vehicles. We suggest a mathematical treat and a methodological treat to reduce the computational load. The mathematical treat is that the dynamics of system is discretized with sparse sampling time without loss of energy balance. The methodological treat is that the efficiency of the hybrid vehicle is inferred by characteristic loss evaluation that is computationally inexpensive. With the suggested methodology, evaluating a design candidate of hybrid powertrain system is taken few minutes, which was taken several hours when dynamic programming is used.

• Journal of Energy Engineering
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• v.19 no.2
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• pp.92-102
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• 2010

Plug-in hybrid electric vehicle(PHEV) is a hybrid electric vehicle (HEV) with more added battery capacity that can be recharged from the electric power grid. Plug-in battery electric vehicle(PBEV) is a pure electric vehicle that uses only electric motor using electricity from battery that recharged from the power grid. PHEV and PBEV requires recharging of batteries in the vehicles from electric power grid. Recently, PHEVs and PBEV are being developed around the world. It is important to understand how these electric vehicles affect power demands and carbon dioxide emissions. From vehicle customer viewpoint, running energy cost will be imporatnt factor to consider. This paper analyzes the potential impacts of PHEVs and PBEVs on electric power demand, and associated CO2 emissions in 2020 with an projection that the vehicles will be penetrated with 10% market share. Energy costs for the vehicles are also calculated and compared with the conventional combustion vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.91-96
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• 2014

nowadays, many researches for plug-in hybrid electric vehicles have been actively carried out to improve the gas mileage in comparison with mass-produced hybrid electric vehicles. In this paper, the on-board charger for plug-in hybrid electric vehicles is studied for obtaining the high efficiency. The on-board charger consists of two phase interleaved PFC circuit and LLC resonant converter. The new design procedures of LLC resonant converter are proposed in this paper. These are very simple and powerful method. In order to verify the abovementioned contents, the LLC resonant converter is designed and tested by using PSIM tool.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.75-81
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• 2017

This paper presents a design and parallel control strategy of 1.8 kW low-voltage DC-DC converter (LDC) for mild hybrid electric vehicles to improve their power density, system efficiency, and operation stability. Topology and control scheme are important on the LDC for mild hybrid electric vehicles to achieve high system efficiency and power density because of their very low voltage and large current in input and output terminals. Therefore, the optimal topological structure and control algorithm are examined, and a detailed design methodology for the power and control stages is presented. A working sample of 1.8 kW LDC is designed and implemented by applying the adopted topology and control strategy. Experimental results indicate 92.45% of the maximum efficiency and 560 W/l of power density.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.97-100
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• 2006

Accelerating ability is one of the most important performance of the vehicle. Unlike conventional internal combustion vehicles and power-assist hybrid vehicles, the maximized acceleration of dual mode hybrid vehicles is not simply. achieved by maximizing engine or motor torque Because of the dynamic stability of planetary gear, speeds and torques control of engine, motor 1 and motor 2 is essential and according to control value, acceleration performance is changed There are two control values which are velocity and torque for each component totalling six. These six values can be variables for an objective function. However, because three velocity variables can be regarded as only one variable speed ratio and the remaining three torque variables can be solved analytically, without complicated numerical algorithm the solution for the objective function can be obtained. This optimized solution shows the best performance possible to the specified dual mode system.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.781-790
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• 2007

Hybrid electric vehicles(HEV) combined with more than one power sources have great potential to improve fuel economy and reduce pollutant emissions. The Integrated Starter Generator(ISG) HEV researched in this paper is a two energy sources vehicle, with a conventional internal combustion engine(ICE) and an energy storage system(batteries). In order to investigate the potential of diesel engine hybrid electric vehicles in fuel economy improvement and emissions reduction, a Dynamic Programming(DP) based supervisory controller is developed to allocate the power requirement between ICE and batteries with the objective of minimizing a weighted cost function over given drive cycles. A fuel-economy-only case and a fuel & emissions case can be achieved by changing specific weighting factors. The simulation results of the fuel-economy-only case show that there is a 45.1% fuel saving potential for this ISG HEV compared to a conventional transit bus. The test results present a 39.6% improvement in fuel economy which validates the simulation results. Compared to the fuel-economy-only case, the fuel & emissions case further reduces the pollutant emissions at a cost of 3.2% and 4.5% of fuel consumption with respect to the simulation and test result respectively.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.651-658
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• 2007

This paper presents a new type of fuzzy logic-based power control strategy for fuel cell hybrid electric vehicles designed to improve their fuel economy while maintaining the battery's state of charge. Since fuel cell systems have inherent limitations, such as a slow response time and low fuel efficiency, especially in the low power region, a battery system is typically used to assist them. To maximize the advantages of this hybrid type of configuration, a power distribution control strategy is required for the two power sources: the fuel cell system and the battery system. The required fuel cell power is procured using fuzzy rules based on the vehicle driving status and the battery status. In order to show the validity and effectiveness of the proposed power control strategy, simulations are performed using a mid-size vehicle for three types of standard drive cycle. First, the fuzzy logic-based power control strategy is shown to improves the fuel economy compared with the static power control strategy. Second, the robustness of the proposed power control strategy is verified against several variations in system parameters.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.539-542
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• 2006

Many researches about next generation vehicles are trending toward HEV which has better fuel economy than an internal-combustion engine. But existing HEV has some defects at specific running states(eg. highway running It is possible that dual-mode hybrid system overcomes that defects. Mode change parameter, ${\gamma}$ helps to analyse the mode changing of dual mode hybrid and is applied at a numerical analysis on testing the performance. There is an additional constraint when vehicles drive on engine mode. No power assistance of battery applies on engine mode. Because vehicles must be sustained by only engine power while vehicle drives on constant speed mode. At the conclusion of this paper, graphs show the ability of motors that satisfy the equilibrium of the lever system. Designers can roughly determine capacities of the motors, parameters of the lever system by this analysing method.