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Today, much information from traffic infrastructures and sensors of ego vehicle is available. Using such information has a potential for internal combustion engine vehicle to reduce fuel consumption in real world. In this paper, a powertrain controller for a hybrid electric vehicle aiming to reduce fuel consumption is introduced, which uses information from traffic signals, the global positioning system and sensors, and the preceding vehicle. This study was carried out as a benchmark problem of engine and powertrain control simulation and modeling 2021 (E-COSM 2021). The developed controller firstly decides reference acceleration of the ego vehicle using the traffic signal and the position information and the preceding vehicle speed. The acceleration and deceleration leading to increase in unnecessary fuel consumption is avoided. Next, the reference engine, generator, and motor torques are decided to achieve the reference acceleration and minimize fuel consumption. In addition, the reference engine, generator and motor torques were decided by the given fuel consumption map for the engine, and by the virtual fuel consumption maps for the generator and the motor. The virtual fuel consumption is derived from the efficiency maps of the generator and the motor using a given equivalent factor, which converts electricity consumption to fuel for the generator and the motor. In this study, a controller was designed through the benchmark problem of E-COSM 2021 for minimizing total fuel consumption of the engine, the generator, and the motor. The developed controller was evaluated in driving simulations. The result shows that operating the powertrain in efficient area is a key factor in reducing total fuel consumption.

The purpose of this study is to develop a model for the gas exchange process in a rebreathing homogeneous charge compression ignition (HCCI) engine. HCCI engines are attracting significant attention due to their low emissions and high efficiency. To design the control system of an HCCI engine, it is necessary to develop a control-oriented engine model. The developed model lowers its computational load by combining two types of models. The model consists of a discrete model for the exhaust process (the first half of the gas exchange process) and a continuous model with a variable calculation step size for the rebreathing process (the latter half of the gas exchange process). Also, the constructed model maintained its prediction accuracy, as the pressure pulsation in the exhaust port was modeled, and an unsteady flow equation was used. It was confirmed that the model developed for the gas exchange process calculated in about half time of one cycle and reproduced the results of 1D engine simulation software with a maximum error of about 10% in the in-cylinder pressure, temperature, and trapped mass.

In stand-alone operations, on-site generators must balance and meet demand at any time for second-by-second fluctuations in output and load demand. However, the previous optimization tool for private generator configuration in hospital buildings did not consider demand sufficiency. Herein, this qualitative electricity problem was solved by proposing a new optimization method that considers the balance of power supply and demand in the stand-alone operation of on-site generators during power outages. As a demand sufficiency condition, a power balance simulator obtained available configurations of private generators that can be operated within the standard alternating current (AC) frequency range of 49–51 Hz. We also compared case study results by applying these constraints to the findings of earlier studies. The same case study from an earlier paper reported that the optimal amount of photovoltaic systems installed is approximately the upper limit (set at 600 m2 in this calculation) and the optimal solution. In contrast, the optimization results with additional constraints to keep frequency fluctuations within specified limits yielded an optimal value significantly less than the previous optimization; one case study showed that the optimal installation amount of photovoltaics was 0 m2. However, the key equipment in this study was the emergency diesel generator. The emergency generator compensates for power shortages and balances supply and demand under power outages. The results suggest that case studies with demand-satisfying conditions tend to select equipment configurations that effectively improve the expected power shortage rate.

In hospitals, the energy supply is the key to ensuring modern medical care even during power outages due to a disaster. This study qualitatively examined whether the supply–demand balance can be stabilized by the private generator prepared by the hospital building during stand-alone operations under disaster conditions. In the nanogrid of the hospital building, the power quality was examined based on the AC frequency, which characterizes the supply–demand balance. Gas engine generators, emergency diesel generators, photovoltaic panels, and storage batteries were presumed to be the private generators in the hospital building. The output reference values for the emergency diesel and gas engine generators were set using droop control, and the C/D controller-enabled synchronized operation. In addition, to keep the AC frequency fluctuation minor, the photovoltaic panels were designed to suppress the output fluctuation using storage batteries. As a result of case studies, the simulator predicts that the frequency fluctuation varies greatly depending on the weather conditions and the fluctuation suppression parameters, even for the same configuration with the same power generation capacity. Therefore, it is preferable to increase the moving average time of the output and reduce the feedback gain of the storage battery to suppress the output fluctuation from the photovoltaics. However, there is a trade-off between suppressing the output fluctuation and the minimum required storage capacity. Furthermore, since the photovoltaics’ output varies with the weather, other private generators’ capacity and control parameters significantly impact power quality. The simulator proposed in this study makes it possible to study each hospital's desirable private generator configuration.

From previous combustion oscillation experiments using a simulated gas turbine combustor, oscillation frequencies around 350 Hz were measured in only natural gas-fired, and around 200 and 400 Hz were measured in the case of hydrogen-containing fuel. In this study, the axial gas column vibration mode was assumed, and the method to reproduce the change of oscillating frequency due to the difference of fuel was investigated. In the previous study, the temperature distribution in the combustor was divided into only two regions, and there were problems in terms of parameter estimation for modeling the flame dynamics. Therefore, the transfer matric method that incorporates a linear temperature gradient was employed. Also, the temperature distributions obtained from computational fluid dynamics, and experiments were reduced to one dimension to reproduce the difference in combustion characteristics due to the difference in fuel composition; four methods were proposed, the axial representative temperatures. The Nyquist plot method was used to calculate up to 10 combinations of resonant frequency and growth rate simultaneously. Furthermore, the oscillation frequency was determined in which the resonance frequency with the growth rate was maximum. As a result, the value of the oscillating frequency obtained differed depending on creating the representative temperature distribution.

Model-based control systems are drawing attention in relation to implementing advanced combustion technologies with high thermal efficiency and low emissions, such as homogeneous charge compression ignition and premixed charge compression ignition combustion, having low robustness. A model-based control system for engine combustion derives control inputs based on reference values and operating conditions in each cycle. Thus, it can replace the conventional control map, which necessitates a significant number of experiments. However, model-based control for combustion requires reference values, such as heat-release-rate peak timing and value, which represent the combustion state. In addition, because model-based control systems derive control inputs cycle by cycle, the combustion reference for the transient condition is critical for maximizing the benefit of such systems. Therefore, this study describes a design method of the combustion reference values for transient operation. The combustion method targeted in this study is a premixed compression ignition combustion that exhibits two-stage heat releases and can reduce combustion noise. Particularly, a method using predicted future operating conditions considering the driving characteristics is proposed. Designed combustion reference values with the proposed method were evaluated with engine control experiments in a certain part of worldwide harmonized light vehicles test cycle. Results indicate that the rate of achieving the desired two-stage heat releases combustion improved from 57% to 81% and combustion noise reduced. Thus, designing the combustion reference values for transient operation by considering future operating conditions is effective to ensure advanced combustion. In addition, such a method can consider the driving characteristics.

Model based control with physical models are proposed as an alternative to conventional control methods to improve engine performance under real driving conditions including various transient condition. Even if models are built based on physical rules, the models still have several parameters which is desirable to adapt in real time according to driving condition. Therefore, the authors developed an online automatic adaptation method for model-based control of diesel engines, which is based on neural networks. The predictive accuracy of the adapted model has been evaluated by simulation, and the performance of the feed-forward controller based on the model is evaluated by experiment under actual engine.

text, 学術雑誌論文 / Journal Article, In this study, we propose a design method of a model-based nonlinear feedforward controller for a diesel engine air-path system. First, a physical air-path model of the diesel engine was developed. Then, a feedforward controller was developed based on the inverse characteristics of the developed physical model. To improve the transient responses of the boost pressure and EGR ratio, the response delay of the turbocharger and manifolds dynamics were considered while designing the feedforward controller. The effectiveness of the proposed method was evaluated by conducting experiments using a real diesel engine. The experimental results indicated a good tracking performance for both the boost pressure and EGR ratio.

It is essential to secure energy sources by installing a private power generator for business continuity in a power outage. The authors have developed an optimization tool to estimate the optimal amount of distributed power supply equipment using economic efficiency and resilience as two evaluation indicators. However, it is questionable whether the private generator in a hospital building can generate sufficient electricity to meet demands in case of a power failure, because demand has short cycle fluctuations on the order of seconds, and the private generator must respond to these fluctuations from time to time in the case of stand-alone operation. The optimization tools we have developed in the past have not considered the balance between power output and load demand (demand sufficiency). Therefore, this paper proposes a new optimization method that considers balancing power supply and demand in private generators’ independent operation during power outages. We narrowed the optimization constraints as demand sufficiency conditions: standard AC frequency range between 49 and 51 Hz. More practical optimal solutions are obtained by applying the new constraints to the multi-optimization. We also compare the case study results by applying these constraints to the results of previous case studies.

A combustion oscillation experiment fueling a mixture of hydrogen and natural gas was performed. The results showed oscillating frequencies of around 350 Hz in the case of the town gas only, whereas oscillating frequencies of around 200 and 400 Hz were observed in the hydrogen-containing fuel case. We hypothesized that the oscillating frequencies shift may occur by changing the temperature-distribution inside the tube, which was caused by different combustion conditions with the fuel mixture. As a result, the possible oscillating frequencies of not only around 350 Hz but also around 200 and 400 Hz were obtained. Although three types of possible oscillating frequencies were obtained in our previous study, more detailed temperature distributions should be considered to clarify the effect of the changing fuel mixture composition. In this paper, representative one-dimensional temperature distributions were formed by the combination of measured and calculated temperature distributions in the combustion tube for the corresponding fuel mixture. To include the detailed temperature distributions, the acoustic network model was divided into enough small elements to express the temperature distributions, where each element was connected by the transfer matrix. Then, the possible oscillating frequencies were calculated, taking account of the influence of the temperature distributions.

Lean-burn gas engines have recently attracted attention in the maritime industry, because they can reduce NOx, SOx, and CO2 emissions. However, since methane (CH4) is the main component of natural gas, the slipped methane, which is the unburned methane, likely contributes to global warming. It is thus important to make progress on exhaust after-treatment technologies for lean-burn gas engines. A Palladium (Pd) catalyst for CH4 oxidation is expected to provide a countermeasure for the slipped methane, because it can activate at lower exhaust temperature comparing with platinum. However, a de-activation in higher water (H2O) concentration should be overcome because H2O inhibits CH4 oxidation. This study was performed to investigate the effects of exhaust temperature or gas composition on active Pd catalyst sites to clarify CH4 oxidation performance in the exhaust gas of lean-burn gas engines. The authors developed the method of estimating effective active sites for the Pd catalyst at various exhaust temperatures. The estimation method is based on the assumption that active sites used for CH4 oxidation process can be shared with the active sites used for carbon mono-oxide (CO) oxidation. The molecular of chemisorbed CO on the active sites of the Pd catalyst can provide effective active sites for CH4 oxidation process. This paper introduces experimental results and verifications of the new method, showing that chemisorbed CO volume on a Pd/Al2O3 catalyst is increased with increasing Pd loading in 250–450 °C, simulated as a typical exhaust temperature range of lean-burn gas engines.

Although many studies have been carried out using control-oriented engine models for advanced combustion technologies, methods of adapting model parameters for these models have still not been considerably studied. In this paper, we propose a method to adapt model parameters for an ignition model and a combustion model of a physics-based discrete diesel engine model using neural networks. Using experimental data on an engine bench as well, we examined how to perform adapting and training, such as optimization algorithms, how to select training data, appropriate feature values, and algorithms for switching the neural networks according to the operating regions. As a result, this adaptation method was able to improve the prediction accuracy of the heat release rate of pre-combustion better than when adapted using the previous adaptation method and when the model parameters were fixed.

In this study, a multiple-input multiple-output feedforward controller for use with multiple-point fuel injection systems is applied to a diesel engine using an original control-oriented model. The target-tracking performance of this multiple-input multiple-output feedforward controller was then tested in terms of how well the controller adjusts the fuel delivery ratios to the pilot injection, pre-injection, main fuel injection, and the main fuel injection timing, and controls the in-cylinder peak pressure and its timing. Control experiments are conducted at different engine outputs and speeds while changing the targets of the in-cylinder peak pressure and its timing. The controller is able to track the varying targets within an acceptable error included in the original model. The calculation time, which is almost double that of a single-input single-output controller, is sufficiently fast to derive the applicable inputs.

In 2017, the Mistry of Health, Labor, and Welfare in Japan added a requirement for domestic disaster base hospitals to install electric power generation equipment with a generation capacity at least 60% of usual demand for securing business continuity. In this study, we developed a multi-objective optimization tool for assisting the determination of the capacity of distributed generation equipment and contract plans considering energy-resiliency after a disaster. The selected objective functions are a total cost representing economy and environment, and an expected value of power shortage ratio after the catastrophe representing energy-resiliency. As a result, our developed tool could obtain the Pareto-optimal solutions for various size hospitals on the parameter plane of the two objective functions. As well as total costs, for all optimal solutions, the expected value of power shortage ratio under disaster situation resulted in less than 40% suggesting that the national requirement standard is satisfied. Then, the cluster analysis was carried out to grasp the tendency of optimal solutions. From the analysis of average value for each cluster, it is shown that the optimal introductory capacities of gas engine generators and storage batteries couple through the outage probabilities of gas supply. Furthermore, the optimal capacity of photovoltaic is much larger than the one assumed to install on the estimated rooftop area of the hospital building, which suggests that hospital can take an option to introduce more photovoltaics to an adjacent area if possible.

This paper deals with a combustion control system design problem for diesel engines. The consider combustion in this paper is a premixed diesel combustion which produce a dual peak heat release rate. This combustion has high thermal efficiency and low NOx and PM emissions. However, in order to implement this combustion, it is required to design a robust combustion control system because this combustion is low robust with respect to changes of the engine state. Therefore, in this paper, we design an adaptive output feedback control system by considering the in-cylinder heat release rate as the output to be controlled. The effectiveness of the proposed method is confirmed through numerical simulations and experiments on a practical diesel engine.

text, 学術雑誌論文 / Journal Article, In this research, we developed a two-degree-of-freedom control system for a Diesel engine air path system. First, a physical air path model of the Diesel engine was developed. Then, a feedforward controller was designed based on the inverse of the developed physical model, thus reducing the computational effort in real-time calculation. The feedback controller was designed by using an H∞ control theory by regarding the plant nonlinearities and the response delay of the actuators as uncertainties to the nominal model. The feedforward and feedback controllers were implemented as a two-degree-of-freedom control scheme. Further, an anti-windup scheme was introduced in the feedback controller to reduce the overshoot in the intake manifold pressure response. The effectiveness of the proposed method was evaluated by conducting not only simulations using the nonlinear physical model, but also experiments using a real Diesel engine.

The Olympic Games will be held in Tokyo in 2020 and the period will be the hottest period of the year in Japan. Marathon is a sport with a large heat load, and it is said that the risk of heat stroke rises more than other sports activities. The thermal environment of the 2020 Tokyo Olympic marathon course is analyzed by using wet-bulb globe temperature (WBGT) and Universal Thermal Climate Index (UTCI) map of the center area of Tokyo. The change due to the place, the effect of the shadow of the building, and the position on the course was analyzed from the distribution of WBGT and UTCI in the short-term analysis of sunny day from August 2 to August 6, 2014. To make the distribution map, we calculated distributions of sky view factor and mean radiant temperature of the 10 km × 7.5 km analyzed area in the center of Tokyo. Distributions of air temperature and humidity are calculated from Metropolitan Environmental Temperature and Rainfall Observation System data, which is a high-resolution measurement network. It was possible to incorporate the local variation of temperature and humidity of the analyzed area. In the result, the WBGT is about 1 °C lower and the UTCI is about 4-8 °C lower in the shadow of buildings from 9:00 to 10:00 than in the sunny side. As a cooling method, making a shadow is a relatively effective method. The variation along the course considering the distribution of meteorological data within the area is about 0.5 °C WBGT and 1 °C UTCI range. If we allow the error of this range, one-point meteorological data can be applied for the estimation along the course. Passing the right side (left side in the case of return) of the course could keep the accumulated value slightly lower along the course in the morning because the marathon course roughly runs from west to east and buildings' shadow is on the relatively right side (south side). But practically, the effect of changing the position on the course was small. The long-term analysis on the degree of risk for each hour was also carried out by using one-point data of the first 10 days of August from 2007 to 2016. The risk increased rapidly after 8:00. It will be safer if the marathon race is finished before 9:00 or if the race is held after 19:00.

Subsidy and social systems should be designed to effectively promote, for example, the introduction of a mechanical system. For an effective subsidy distribution, developing evidence-based decision-making methodologies is essential. We developed a tool that minimizes an objective function includes economic costs, environmental cost, and disaster risk to determine the amount of energy distributed by the equipment when installing in hospitals against disasters. Open data available on the Internet are used as simulation values herein. This simulation model optimizes six design values using a genetic algorithm based on the values (business site area, demand for heat and electricity, and maximum allowable loss) input by customers for their construction and visualizes the total cost. The tool allows to quantitatively assess the changes in the initial and running costs owing to equipment installation and the avoidable losses related to $$\hbox {CO}_{2}$$ emission reductions and disaster risks. In addition, the net present value (NPV) can be calculated using the obtained values for initial and running costs, thereby allowing to clearly estimate the return on investments after equipment installation. The opportunity profit can be calculated based on the difference between the NPV after 15 years assuming no risk and with disaster risks. A method to set this opportunity profit as a calculated subsidy amount is proposed herein. Decision support can be provided via these simulations to the customers and government subsidy system design engineers.

text, 学術雑誌論文 / Journal Article, Premixed charge compression ignition (PCCI) combustion has a potential to achieve the low emission level while the thermal efficiency remains high. It requires more precise combustion control due to the low robustness of the premixed combustion. In this study, a model-based control system for both air path system and combustion is developed for realizing the ideal PCCI combustion in future. For the air path system control, a feedback (FB) controller based on H∞ control theory is used. In this controller, the nonlinearity of the plant is considered as the perturbation and robustness is ensured by H∞ control. For the combustion control, a feedforward (FF) controller is designed as an inverse model of a discretized combustion model. In this controller, the inverse model is updated cycle by cycle on-board to consider the variation of combustion characteristics depending on operation condition. The performance of the overall control system including both controllers is evaluated by the reference following test under the transient mode operation in both the simulation and the experiment for PCCI-like combustion with advanced fuel injection timing. The control system showed good tracking performance both in air path and combustion systems and the availability of the model-based control system is shown.

In order to realize stable and fuel-efficient operation with homogeneous charge compression ignition (HCCI) combustion, it is necessary to precisely control in-cylinder conditions such as gas temperature and oxygen concentration according to the target load set for each cycle. The HCCI combustion discussed in this study utilizes internal exhaust gas recirculation (EGR). For this type of combustion, the exhaust gas temperature and composition in the last cycle should be accurately estimated, and the internal EGR rate and the fuel injection quantity should be appropriately commanded to generate in-cylinder conditions that ensure combustion in the next cycle. To implement this effectively, the authors constructed a control-oriented model for the HCCI combustion which utilizes internal EGR with the negative valve overlap method, and developed a model-based feedforward controller based on this model. Firstly, the model-based feedforward controller was validated by simulations in which a change in the target load was given to the controller. Secondly, engine experiments were conducted to validate the controller in the same way. The results confirmed that the model-based feedforward controller was able to generate in-cylinder conditions suitable for the target load given to each cycle and thus realize stable HCCI combustion while following the target load.

We developed a feed-forward controller for a conventional diesel combustion engine with triple fuel injection and experimentally evaluated its performance. A combustion model that discretizes an engine cycle into a number of representative points to achieve a light calculation load is embedded into the controller; this model predicts the in-cylinder gas-pressure-peak timing with information about the operating condition obtained from the engine control unit. The controller calculates the optimal main-fuel-injection timing to control the in-cylinder gas-pressure peak using the prediction result as a controller with a single input and output. The controller’s performance was evaluated by experiments using a four-cylinder diesel engine under changing the target value of the in-cylinder gas-pressure-peak timing during a target-following test and the performance was also evaluated under changing the exhaust gas recirculation ratio at the constant target value of the in-cylinder gas-pressure-peak timing for the disturbance-response test. It was found that the controller could calculate the optimal main-injection timing over a cycle and maintain the targeted in-cylinder gas-pressure-peak timing even when the target value or exhaust gas recirculation changed. The combustion model was also shown to be fast enough at predicting diesel combustion for onboard control.

Engine systems must continuously increase their thermal efficiencies and lower their emissions in real operation. To meet these demands, engine systems are increasingly improving their transient performance through control technology. Conventional engine control systems depend on control maps obtained from huge numbers of experiments, which is necessarily limited by the available number of man-hours. These time-consuming control maps are now being replaced by control inputs derived from on-board models. By calculating optimized control inputs in real time using various information, model-based control increases the robustness of advanced combustion technologies such as premixed charge compression ignition and homogeneous charge compression ignition, which use auto-ignition and combustion of air–fuel mixtures. Models also incur relatively low computational loads because the specifications of the engine control unit are lower than those of current smartphones. This article develops a simple diesel combustion model with model-based control of the multiple fuel injections. The model employs the discretized cycle concept based on fundamental thermodynamic equations and comprises simple fuel injection and chemical reaction models. Our control concept aims mainly to decrease the fuel consumption by increasing the thermal efficiency and reduce the combustion noise in real-world operation. The model predicts the peak in-cylinder gas pressure and its timing that minimize the combustion noise and maximize the thermal efficiency, respectively. In an experimental validation of the model, the computed and measured in-cylinder pressures were well matched at each phase under various parameter settings. In addition, the calculation time of the model is sufficiently short for on-board applications. In future, the proposed model will be extended to the design and installation of controllers for engine systems. The control concept and associated problems of this task are also described in this article.

Thermal image is important source of information in the urban climate. In this study, we proposed “structure-from-motion (SfM) thermal mosaicing” which uses only thermal images to make orthogonal land surface temperature (LST) image in the process of SfM. With this method, orthogonal LST image can be made automatically without finding many ground control points manually. For the application of the method, LST images of central Tokyo in the summer of 2007 and 2013 were made. The quality of the images was practically precise. The images were compared and it is clearly shown that the LST in 2013 became cooler than in 2007 in many areas of development. There were also hotter areas where loss of green spaces was observed. With prevailing usage of drones for obtaining airborne LST image, this automatic method to make LST image will be very useful for UHI studies and urban planning.

Lean-burn gas engines have recently attracted attentions in the maritime industry, because they can reduce NOx, SOx and CO2 emissions. However, since methane (CH4) is the main component of natural gas, the slipped methane which is the unburned methane emitted from the lean-burn gas engines likely contributes to global warming. It is thus important to make progress on exhaust aftertreatment technologies for lean-burn gas engines. A Palladium (Pd) catalyst for CH4 oxidation is expected to provide a countermeasure for slipped methane, because it can activate at lower exhaust gas temperature. However, a deactivation in higher water (H2O) concentration should be overcome, because H2O inhibits CH4 oxidation. This study was performed investigates the effects of exhaust gas temperature or gas composition on active Pd catalyst sites to clarify CH4 oxidation performance in the exhaust gas of lean-burn gas engines. The authors developed the method of estimating effective active sites for the Pd catalyst at various exhaust gas temperature. The estimation method is based on the assumption that active sites used for CH4 oxidation process can be shared with the active sites used for Carbon mono-oxide (CO) oxidation. The molecular of chemisorbed CO on the active sites of the Pd catalyst can provide effective active sites for CH4 oxidation process. To clarify the effects of exhaust gas temperature and compositions on active Pd catalyst sites, the authors developed an experimental system for the new estimation method. This paper introduces experimental results and verifications of the new method, showing that chemisorbed CO volume on a Pd/Al2O3 catalyst is increased with increasing Pd loading in 250–450 °C, simulated as a typical exhaust gas temperature range of lean-burn gas engines. The results provide a part of the criteria for the application of Pd catalysts to the reduction of slipped methane in exhaust gas of lean-burn gas engines.

This paper proposes a scheme, called the disaster-risk-weighted damage inequality, for a customer to perform introductory planning for a distributed generation system considering business continuity planning in a disaster case. To calculate this inequality, the relevant disaster risks are surveyed and system operating simulations for target buildings such as a hotel, a hospital, a large-scale office, and a collective housing building are performed by solving a mixed integer linear programming problem under the assumption that a cogeneration system is installed as a distributed generation system. Next, we determined the probabilities of a disaster occurrence and business interruption due to a disaster, the initial cost of the equipment, the running cost, and the reduction in running cost due to a cogeneration system installation. The cogeneration system was found to effectively reduce the running cost. Finally, the suggested inequality is calculated and determined whether it is satisfied. The result showed that cogeneration system installation very effectively reduces the running cost for a hotel, a hospital, and a large-scale office, compared to the tolerable amount of loss that is preliminarily determined by a customer.

Diesel engines exhibit highly efficient, environmentally sound performance under good operational control; however, because of the demand of controlling multiple actuators under various environmental conditions, the conventional experimental method for controlling diesel engines has become increasingly difficult. Therefore, diesel combustion models with less calculation loads were ultimately developed with the aim of implementing such model-based controllers for engine control unit in the future. To achieve the on-board application of the diesel combustion model, the in-cylinder state of a single cycle was discretized into several representative phases such as a valve-opening and valve-closing phase, ignition phase, and maximum pressure phase. Temperature and oxygen quantities in residual gas were considered as the state variables of the system because they have a critical effect on combustion and induce cyclic coupling. The model could take account of the effect of actuators in diesel engines, and the states in each phase were calculated by fundamental thermodynamic equations and some empirical equations. The model was validated against experimental results and had a good agreement with in-cylinder pressures and temperatures at each phase. In addition, the calculation times of the model were confirmed to be capable of on-board application. Furthermore, as a demonstrative example and to show the added value of the model, it was used to synthesize controllers to enable multi-input/multi-output control of a diesel engine in simulation.