CI Engine Model Predictive Control With Availability Destruction Minimization

2018 ◽  
Author(s):  
Muataz Abotabik ◽  
Richard T. Meyer
Keyword(s):  
Energy Source ◽  
Model Predictive Control ◽  
Fuel Consumption ◽  
Predictive Control ◽  
Alternative Fuels ◽  
Combustion Engine ◽  
Tracking Error ◽  
Specific Fuel Consumption ◽  
Nox Emissions ◽  
Compression Ignition Engine

Major interests in the automotive industry include the use of alternative fuels and reduced fuel usage to address fuel supply security concerns and regulatory requirements. The majority of previous internal combustion engine (ICE) control strategies consider only the First Law of Thermodynamics (FLT). However, FLT is not able to distinguish losses in work potential due to irreversibilities, e.g., up to 25% of fuel exergy may be lost to irreversibilities. To account for these losses, the Second Law of Thermodynamics (SLT) is applicable. The SLT is used to identify the quality of an energy source via availability since not all the energy in a particular energy source is available to produce work; therefore optimal control that includes availability may be another path toward reduced fuel use. Herein, Model Predictive Control (MPC) is developed for both FLT and SLT approaches where fuel consumption is minimized in the former and availability destruction in the latter. Additionally, both include minimization of load tracking error. The controls are evaluated in the simulation of a single cylinder naturally aspirated compression ignition engine that is fueled with either 20% biodiesel and 80% diesel blend or diesel only. Control simulations at a constant engine speed and changing load profile show that the SLT approach results in higher SLT efficiency, reduced specific fuel consumption, and decreased NOx emissions. Further, compared to use of diesel only, use of the biodiesel blend resulted in less SLT efficiency, higher specific fuel consumption, and lower NOx emissions.

An Energy Management Strategy for Power-split Hybrid Electric Vehicle using Model Predictive Control

2021 ◽  
Vol 18 (4) ◽  
Author(s):  
Muhammad Zahid ◽  
Naseer Ahmad
Keyword(s):  
Model Predictive Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Energy Management ◽  
Predictive Control ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Specific Fuel Consumption ◽  
Power Split ◽  
Hybrid Electric

To fulfil future demand for energy and to control pollution, a power-split hybrid electric vehicle is a promising solution combining attributes of a conventional vehicle and an electric vehicle. Since energy is available from two subsystems i.e, engine and battery, there is the freedom to manage it optimally. In this work, model predictive control strategy, that has the constraint handling which makes it a better choice over other strategies for efficient energy management of hybrid electric vehicles. A detailed mathematical model of the power split configured hybrid electric vehicle is developed that encompasses the engine, planetary gear, motor/generator, inverter, and battery. An interior-point optimizer based-nonlinear model predictive control strategy is applied to the developed model by incorporation of operational constraints and cost function. The objective is to curtail fuel consumption while the battery’s state of charge should be maintained within predefined limits. The complete developed model was simulated in MATLAB for motor, generator, engine speed, and battery SoC. Computed specific fuel consumption from the proposed MPC during the NEDC and the HWFET cycles are 4.356liters/100km and 2.474 litres/100 km, respectively. These findings are validated by the rule-based strategy of ADVISOR 2003 that provides 4.900 litres/100 km and 3.600 litres/100 km over the NEDC and the HWFET cycles, respectively. This indicates that the proposed MPC shows 11.11 % and 31.26 % improvement in specific fuel consumption in the NEDC and HWFET drive cycles respectively.

Compensatory model predictive control for post-impact trajectory tracking via active front steering and differential torque vectoring

2020 ◽  
pp. 095440702097908
Author(s):  
Mingcong Cao ◽  
Chuan Hu ◽  
Rongrong Wang ◽  
Jinxiang Wang ◽  
Nan Chen
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
Tracking Error ◽  
Collision Probability ◽  
Critical Conditions ◽  
Physical Analysis ◽  
Compensatory Model ◽  
Torque Vectoring ◽  
Post Impact

This paper investigates the trajectory tracking control of independently actuated autonomous vehicles after the first impact, aiming to mitigate the secondary collision probability. An integrated predictive control strategy is proposed to mitigate the deteriorated state propagation and facilitate safety objective achievement in critical conditions after a collision. Three highlights can be concluded in this work: (1) A compensatory model predictive control (MPC) strategy is proposed to incorporate a feedforward-feedback compensation control (FCC) method. Based on the definite physical analysis, it is verified that adequate reverse steering and differential torque vectoring render more potentials and flexibility for vehicle post-impact control; (2) With compensatory portions, the deteriorated states after a collision are far beyond the traditional stability envelope. Hence it can be further manipulated in MPC by constraint transformation, rather than introducing soft constraints and decreasing the control efforts on tracking error; (3) Considering time-varying saturation on input, input rate, and slip ratio, the proposed FCC-MPC controller is developed to improve faster deviation attenuation both in lateral and yaw motions. Finally two high-fidelity simulation cases implemented on CarSim-Simulink conjoint platform have demonstrated that the proposed controller has the advanced capabilities of vehicle safety improvement and better control performance achievement after severe impacts.

Two-Stroke Marine Diesel Engine Variable Injection Timing System Performance Evaluation and Optimum Setting for Minimum Fuel Consumption at Acceptable NOx Levels

2014 ◽  
Author(s):  
Dimitrios T. Hountalas ◽  
Spiridon Raptotasios ◽  
Antonis Antonopoulos ◽  
Stavros Daniolos ◽  
Iosif Dolaptzis ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Fuel Consumption ◽  
Engine Performance ◽  
Operating Conditions ◽  
Specific Fuel Consumption ◽  
Injection Timing ◽  
Nox Emissions ◽  
Pressure Measurements ◽  
Cylinder Pressure ◽  
Start Of Injection

Currently the most promising solution for marine propulsion is the two-stroke low-speed diesel engine. Start of Injection (SOI) is of significant importance for these engines due to its effect on firing pressure and specific fuel consumption. Therefore these engines are usually equipped with Variable Injection Timing (VIT) systems for variation of SOI with load. Proper operation of these systems is essential for both safe engine operation and performance since they are also used to control peak firing pressure. However, it is rather difficult to evaluate the operation of VIT system and determine the required rack settings for a specific SOI angle without using experimental techniques, which are extremely expensive and time consuming. For this reason in the present work it is examined the use of on-board monitoring and diagnosis techniques to overcome this difficulty. The application is conducted on a commercial vessel equipped with a two-stroke engine from which cylinder pressure measurements were acquired. From the processing of measurements acquired at various operating conditions it is determined the relation between VIT rack position and start of injection angle. This is used to evaluate the VIT system condition and determine the required settings to achieve the desired SOI angle. After VIT system tuning, new measurements were acquired from the processing of which results were derived for various operating parameters, i.e. brake power, specific fuel consumption, heat release rate, start of combustion etc. From the comparative evaluation of results before and after VIT adjustment it is revealed an improvement of specific fuel consumption while firing pressure remains within limits. It is thus revealed that the proposed method has the potential to overcome the disadvantages of purely experimental trial and error methods and that its use can result to fuel saving with minimum effort and time. To evaluate the corresponding effect on NOx emissions, as required by Marpol Annex-VI regulation a theoretical investigation is conducted using a multi-zone combustion model. Shop-test and NOx-file data are used to evaluate its ability to predict engine performance and NOx emissions before conducting the investigation. Moreover, the results derived from the on-board cylinder pressure measurements, after VIT system tuning, are used to evaluate the model’s ability to predict the effect of SOI variation on engine performance. Then the simulation model is applied to estimate the impact of SOI advance on NOx emissions. As revealed NOx emissions remain within limits despite the SOI variation (increase).

Characteristics of Water-in-Diesel Emulsions in a Single Cylinder Compression Ignition Engine

2014 ◽  
Author(s):  
Teja Gonguntla ◽  
Robert Raine ◽  
Leigh Ramsey ◽  
Thomas Houlihan
Keyword(s):  
Fuel Consumption ◽  
Direct Injection ◽  
Engine Performance ◽  
Operating Conditions ◽  
Specific Fuel Consumption ◽  
Brake Specific Fuel Consumption ◽  
Compression Ignition Engine ◽  
Oil Emulsion ◽  
Single Cylinder ◽  
Performance And Emission

The objective of this project was to develop both engine performance and emission profiles for two test fuels — a 6% water-in-diesel oil emulsion (DOE-6) fuel and a neat diesel (D100) fuel. The testing was performed on a single cylinder, direct-injection, water-cooled diesel engine coupled to an eddy current dynamometer. Output parameters of the engine were used to calculate Brake Specific Fuel Consumption (BSFC) and Engine Efficiency (η) for each test fuel. DOE-6 fuels generated a 24% reduction in NOX and a 42% reduction in Carbon Monoxide emissions over the tested operating conditions. DOE-6 fuels presented higher ignition delays — between 1°-4°, yielded 1%–12% lower peak cylinder pressures and produced up to 5.5% lower exhaust temperatures. Brake Specific Fuel consumption increased by 6.6% for the DOE-6 fuels as compared to the D100 fuels. This project is the first research done by a New Zealand academic institution on water-in-diesel emulsion fuels.

Nonlinear Model Predictive Control for Automatic Train Operation with Actuator Saturation and Speed Limit

2014 ◽  
Vol 678 ◽  
pp. 377-381
Author(s):  
Long Sheng Wang ◽  
Hong Ze Xu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
High Speed ◽  
Actuator Saturation ◽  
Tracking Error ◽  
Nonlinear Model Predictive Control ◽  
Speed Limit ◽  
Speed Tracking ◽  
Automatic Train Operation

This paper addresses a position and speed tracking problem for high-speed train automatic operation with actuator saturation and speed limit. A nonlinear model predictive control (NMPC) approach, which allows the explicit consideration of state and input constraints when formulating the problem and is shown to guarantee the stability of the closed-loop system by choosing a proper terminal cost and terminal constraints set, is proposed. In NMPC, a cost function penalizing both the train position and speed tracking error and the changes of tracking/braking forces will be minimized on-line. The effectiveness of the proposed approach is verified by numerical simulations.

scholarly journals Sensitivity Analysis of the Battery Model for Model Predictive Control: Implementable to a Plug-In Hybrid Electric Vehicle

2018 ◽  
Vol 9 (4) ◽  
pp. 45 ◽  
Author(s):  
Nicolas Sockeel ◽  
Jian Shi ◽  
Masood Shahverdi ◽  
Michael Mazzola
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Predictive Control ◽  
Hybrid Electric Vehicle ◽  
Control Solution ◽  
Current Time ◽  
Battery Model ◽  
Hybrid Electric

Developing an efficient online predictive modeling system (PMS) is a major issue in the field of electrified vehicles as it can help reduce fuel consumption, greenhouse gasses (GHG) emission, but also the aging of power-train components, such as the battery. For this manuscript, a model predictive control (MPC) has been considered as PMS. This control design has been defined as an optimization problem that uses the projected system behaviors over a finite prediction horizon to determine the optimal control solution for the current time instant. In this manuscript, the MPC controller intents to diminish simultaneously the battery aging and the equivalent fuel consumption. The main contribution of this manuscript is to evaluate numerically the impacts of the vehicle battery model on the MPC optimal control solution when the plug hybrid electric vehicle (PHEV) is in the battery charge sustaining mode. Results show that the higher fidelity model improves the capability of accurately predicting the battery aging.

scholarly journals Total Harmonic Distortion Oriented Finite Control Set Model Predictive Control for Single-Phase Inverters

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3467 ◽  
Author(s):  
Po Li ◽  
Ruiyu Li ◽  
Haifeng Feng
Keyword(s):  
Model Predictive Control ◽  
Cost Function ◽  
Predictive Control ◽  
Single Phase ◽  
Tracking Error ◽  
Harmonic Distortion ◽  
Total Harmonic Distortion ◽  
Finite Control ◽  
Control Set ◽  
The Cost

Inverters are commonly controlled to generate AC current and Total Harmonic Distortion (THD) is the core index in judging the control effect. In this paper, a THD oriented Finite Control Set Model Predictive Control (FCS MPC) scheme is proposed for the single-phase inverter, where a optimization problem is solved to obtain the switching law for realization. Different from the traditional cost function, which focuses on the instantaneous deviation of amplitude between predictive current and its reference, we redesign a cost function that is the linear combination of the current fundamental tracking error, instantaneous THD value and DC component in one fundamental cycle (for 50 Hz, it is 0.02 s). Iterative method is developed for rapid calculation of this cost function. By choosing a switching state from a FCS to minimize the cost function, a FCS MPC is finally constructed. Simulation results in Matlab/Simulink and experimental results on rapid control prototype platform show the effect of this method. Analyses illustrate that, by choosing suitable weight of the cost function, the performance of this THD oriented FCS MPC method is better than the traditional one.

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