• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.14-20
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• 2015

The Korea ministry of land, infrastructure and transport set the goal of cutting greenhouse gas emissions from the transport sector by 34.3% relative to the business as usual scenario by 2020. In order to achieve this goal, support is being given to education and information regarding eco-driving. As a practical measure, however, a vehicle control strategy for decreasing fuel consumptions and emissions is necessary. Therefore, this paper presents an optimized driving model in order to decrease fuel consumption. Scenarios were established by driving mode. The speed profile for each scenario applied to Comprehensive Modal Emission Model and then each fuel consumption was estimated. Scenarios and speed variation with the least fuel consumption were derived by comparing the fuel consumptions of scenarios. The optimized driving model was developed by the derived the results. The speed profiles of general driver were collected by field test. The speed profile of the developed model and the speed profile of general driver were compared and then fuel consumptions for each speed profile were analyzed. The fuel consumptions for optimized driving were decreased by an average of 11.8%.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.39-47
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• 2020

This paper introduces a novel system-level framework that derives energy efficient electric vehicle (EV) driving speed profile to extend EV driving range without additional cost. This paper first implements an EV power train model considering forces acting on a driving vehicle and motor efficiency. Then, it derivate the minimum-energy driving speed profile for a given driving mission defined by the route. This framework first formulates an optimization problem and uses the dynamic programming algorithm with a weighting factor to derive a speed profile minimizing both of energy consumption and driving time. This paper introduces various weighting factor tracking methods to satisfy the driving time constraint. Simulation results show that runtime of the proposed scaling algorithm is 34% and 50% smaller than those of the binary search algorithm and greedy algorithm, respectively.

• Journal of ILASS-Korea
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• v.28 no.4
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• pp.184-190
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• 2023

The European Union has instituted a new emission standard protocol that necessitates real-time measurements from vehicles on actual roads. The adequate development of routes for real driving emissions (RDE) mandates substantial resources, encompassing both vehicles and a portable emission measurement system (PEMS). In this study, a simulation tool was utilized to predict the vehicle speed traversing the routes developed for the RDE measurements. Initially, the vehicle powertrain system was modeled for both a gasoline hybrid vehicle and a gasoline engine-only vehicle. Subsequently, the speed profile for the specified vehicle was constructed based on the RDE route developed for the EURO-6 standard. Finally, the predicted vehicle speed profiles for highway and urban routes were assessed utilizing the actual driving data. The driving model predicted more consistency in the vehicle speed at each driving section. Meanwhile, the human driver tended to accelerate further, and then decelerate in each section, instead of cruising at a predicted section speed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.30-37
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• 2017

When a wheel profile of a train-tram is designed, both train and tram tracks should be considered. This study designed a wheel profile that enables high-speed driving(200km/h) on the train track and low speed driving on the tram track with multiple sharp curves. The study used the approximation optimization method to reduce cost and time, used the sequential quadratic programming method as the optimized algorithm, and the central composite design and response surface method as an approximate model. The optimized wheel shape based on this approximation optimization method reduced wear of the initial wheel showed a better performance in terms of derailment and lateral force.

• Journal of Drive and Control
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• v.12 no.3
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• pp.18-24
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• 2015

The plug-in hybrid electric vehicle has a high fuel economy and can be driven long distances. Its different modes include the electric vehicle, hybrid electric vehicle, and only engine operating mode. A power management strategy is important to determine which mode should be selected. The strategy makes the vehicle more efficient using appropriate power sources for driving. However, the strategy usually needs a driving speed profile which is future driving cycle. If the profile is known, the strategy easily determines which mode is driven efficiently. However, it is difficult to estimate the speed profile for a real system. To address this problem, this paper proposes a new power distribution strategy using a neural network. The average speed and driving range are used as input parameters to train the neural network system. The strategy determines a limit for the use of the battery and the desired power is distributed between the engine and the motor simultaneously. Its fuel economy can increase by improving the basic strategy.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.38-46
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• 2012

This paper discusses the energy consumption for a mid-size electric vehicle(EV) under various conditions. In order to analyze which driving style is more efficient in terms of the system of the EV, we develop the electric vehicle model and apply several types of speed profiles such as different steady speeds, acceleration/deceleration, and a real world driving cycle including the elevation profile obtained from a GPS device. The results show that the energy consumption of the EV is affected by the operating efficiency of components when driving at low speed, while it depends on required power at wheels when driving at high speed. Also this paper investigates the effect of the elevation of a road and the rate of electrical braking on the energy consumption as well as the fuel economy of a conventional vehicle model under the same conditions.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.355-358
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• 1996

Electrical Power System (EPS) of Electric Vehicle which consists of batteries, motor and driving subsystem, has been modeled. A battery model is modeled with an electrical circuit representing a characteristics of real battery. Driving subsystem is modeled as three different level namely exact, average and functional models. Load profile includes road information, speed profile and EV mechanical parameters, which are incorporated into a reference torque in the driving subsystem model. A system model is integrated to simulate the performance of electric vehicle such as energy balance, battery status, and electrical stress of each subsystem.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.122-131
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• 2015

Recently, starting with the deep underground road construction plan in Seobu Expressway, Korea, there area many studies on deep underground roads to be newly built. However, there is an extreme lack of safety standards, which does not consider traffic conditions and road driving characteristics. Therefore, this study reviewed safety elements to reflect in the deep underground road planning by analyzing driving stability of longitudinal tunnels with road environments, which resemble deep underground roads. For comprehensive analysis, the characteristics and causes of the accidents that have occurred in seven longitudinal tunnels with a length of 2km or over in Gangwon area, were collected. Specifically, geometric structures and facilities of each tunnel were investigated. Also, the present state of facility installation and the changes in driving speed of vehicles passing through each tunnel were observed to analyze the causes for the traffic accidents in each tunnel and accident reduction alternatives. It was revealed that the most frequent accidents in the tunnels resulted from the changes of traffic flow due to the abrupt speed reduction of forward vehicles, or the failure in speed control of following vehicles during the traffic congestion situation. Moreover, installing facilities such as plane and longitudinal curves, median strips and marginal strips seem to induce consistent driving speed. These results mean that for accident prevention, speed management must be preceded and there is a need to develop and introduce safety facilities actively to control the driving flow of forward and following vehicles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6274-6281
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• 2015

Radio-based train control system has driving headway shortening effect by real-time train interval control using two-way radio communication between onboard and wayside systems, and reduces facility investment because it does not require any track-circuit. Automatic train protection(ATP), the most significant part of the radio-based train control system, makes sure a safe distance between preceding and following trains, based on real-time train location tracing. In this paper, we propose the overall ATP train interval control algorithm to control the safe interval between trains, and preprocessing-based speed profile calculation algorithm to improve the processing speed of the ATP. The proposed speed profile calculation algorithm calculates the permanent speed limit for track and train in advance and uses as the most restrictive speed profile. If the temporary speed limit is generated for a particular track section, it reflects the temporary speed limit to pre-calculated speed profile and improves calculation performance by updating the speed profile for the corresponding track section. To evaluate the performance of the proposed speed profile calculation algorithm, we analyze the proposed algorithm with O-notation and we can find that it is possible to improve the time complexity than the existing one. To verify the proposed ATP train interval control algorithm, we build the train interval control simulator. The experimental results show the safe train interval control is carried out in a variety of operating conditions.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.1
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• pp.114-120
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• 2012

Eco-driving technique for electric vehicles (EVs) is investigated in this paper. Many findings on EVs have been reported; however, they did not deal with eco-driving from the viewpoint of theoretical study. The authors have developed an energy-saving driving technique - the so-called "eco-driving" technique based on dynamic programming (DP). Optimal speed profile of an EV, which minimizes the amount of total energy consumption, was determined under fixed origin and destination, running time, and track conditions. DP algorithm can deal with such complicated conditions and can also derive the optimal solution. Using the proposed method, simulations were run for some cases. In particular, the author ran simulations for the case of a gradient road with a traffic signal. The optimization model was solved with MATLAB.