Development of a Simple Robotic Driver System (SimRoDS) to Test Fuel Economy of Hybrid Electric and Plug-In Hybrid Electric Vehicles Using Fuzzy-PI Control

Over the past decade, new models of hybrid electric vehicles have been released worldwide, and the fuel efficiency of said vehicles has increased by more than 5%. To further improve fuel efficiency, vehicle manufacturers have made efforts to design modules (e.g., engines, motors, transmissions, and batteries) with the highest efficiency possible. To do so, the fuel economy test process, which is conducted primarily using a chassis dynamometer, must produce reliable and accurate results. To accurately analyze the fuel efficiency improvement rate of each module, it is necessary to reduce the test deviation. When the test conducted by human drivers, the test deviation is somewhat large. When the test is conducted by a physical robot driver, the test deviation is improved; however, these robots are expensive and time-consuming to install and take up considerable amount of space in the driver’s seat. To compensate for these shortcomings, we propose a simple, structured robot system that manipulates electrical signals without using mechanical link structures. The controller of this robot driver uses the widely used PI controller. Although PI controllers are simple and perform well, since the dynamics of each test vehicle is different (e.g., acceleration response), the PI controller has a disadvantage in that it cannot determine the optimal PI gain value for each vehicles. In this work, the fuzzy control theorem is applied to overcome this disadvantage. By using fuzzy control to deduce the optimal value of the PI gain, we confirmed that our proposed system is available to conduct tests on vehicles with different dynamics.

Model-Based Predictive Control and Dithering Control for an Integrated Gasoline Engine and Three-Way Catalytic Converter System

Controls of integrated gasoline engine and after-treatment systems are critical for fuel efficiency improvement and emission regulation. This paper aims to develop novel model-based Three-Way Catalytic converter (TWC) controls to reduce the fuel consumption and tailpipe emissions for a gasoline engine. A model-based dither control and a nonlinear model predictive control (MPC)-based control, are presented, respectively. The proposed TWC dither control utilizes a systematically designed dither cycle configuration (including dithering amplitude, offset, and frequency) based on a control-oriented model, with the capability to adapt the dither cycle configuration to various engine operating conditions. The MPC control can optimize engine air-fuel ratio (AFR) to maintain the oxygen storage of TWC at a desired level and thus meet the tailpipe NOx, CO and HC emission requirements. The efficacies of both model-based TWC controls are validated in simulation with MPC control improving CO emission conversion efficiencies by 8.42% and 4.85% in simplified US06 and UDDS driving cycles, when compared to a baseline dithering-based AFR control. Meanwhile, NOx emission conversion efficiency is maintained above the required limit of 95%, while the fuel efficiency remains at the same level as the baseline control methodology.

Benefit Assessment of Skidder Powertrain Hybridization Utilizing a Novel Cascade Optimization Algorithm

Over the last decade, off-road vehicles have been increasingly hybridized through powertrain electrification in terms of additional electrical machine-based propulsion and battery energy storage, with the goal of achieving significant gains in fuel economy and reductions in greenhouse gases emissions. Since hybrid powertrains consist of two or more different energy sources and may be arranged in many different configurations, there are many open questions in their design and powertrain energy management control, which may have influence on the hybridized powertrain purchase cost and efficiency. This paper presents simple backward optimization models of conventional and hybrid cable skidder powertrains. These models are then used in the optimization of control variables over one forest path in order to find the minimum possible fuel consumption. The optimization results show that 15% fuel efficiency improvement in winching and skid trail driving can be achieved with the selected hybrid powertrain. With that improvement, main hybrid drive components can be paid off in 13 years.

Aerodynamic Study of the Wake Effects on a Formula 1 Car

The high complexity of current Formula One aerodynamics has raised the question of whether an urgent modification in the existing aerodynamic package is required. The present study is based on the evaluation and quantification of the aerodynamic performance on a 2017 spec. adapted Formula 1 car (the latest major aerodynamic update) by means of Computational Fluid Dynamics (CFD) analysis in order to argue whether the 2022 changes in the regulations are justified in terms of aerodynamic necessities. Both free stream and flow disturbance (wake effects) conditions are evaluated in order to study and quantify the effects that the wake may cause on the latter case. The problem is solved by performing different CFD simulations using the OpenFoam solver. The significance and originality of the research may dictate the guidelines towards an overall improvement of the category and it may set a precedent on how to model racing car aerodynamics. The studied behaviour suggests that modern F1 cars are designed and well optimised to run under free stream flows, but they experience drastic aerodynamic losses (ranging from −23% to 62% in downforce coefficients) when running under wake flows. Although the overall aerodynamic loads are reduced, there is a fuel efficiency improvement as the power that is required to overcome the drag is smaller. The modern performance of Ground Effect by means of vortices management represent a very unique and complex way of modelling modern aerodynamics, but at the same time notably compromises the performance of the cars when an overtaking maneuver is intended.

TOWARDS MEETING THE IATA-AGREED 1.5% AVERAGE ANNUAL FUEL EFFICIENCY IMPROVEMENTS BETWEEN 2010 AND 2020: THE CURRENT PROGRESS BEING MADE BY U.S. AIR CARRIERS

The purpose of this paper is to see if airlines in general, and U.S. air-carriers in particular, are meeting their IATA-agreed 1.5% average annual fuel efficiency improvements between 2010 and 2020. To assess the fuel efficiency performance, a quantitative analysis was performed using data provided by ICAO, IATA and the U.S. Bureau of Transportation Statistics (BTS) Form 41 Schedules P 12(a) and T-2. The metric used to assess fuel efficiency is the one advanced by ICAO, namely Litres per Revenue Tonne Kilometre performed. Trends are examined over an extended timeframe to establish annual fuel efficiency improvements. The findings show that the overall performance of U.S. air-carriers from 2010 to 2018 has just met IATA’s 1.5% target with a 1.52% year-upon-year annual fuel efficiency improvement, with domestic operations showing a greater level of improvement than international operations. Such performance suggests that the U.S.A, and by inference, the rest of the world, are just likely to meet their IATA target by 2020. This achievement has largely been made possible through industry’s tremendous efforts to enhance aircraft engine technologies, implement operational improvements, and reduce airframe weight through the extensive application of composite materials.

Methodology of Excavator System Energy Flow-Down

Due to the strengthening of air-quality regulations, researchers have been investigating methods to improve excavator energy efficiency. Many researchers primarily conducted simulation studies employing mathematical models to analyze the energy consumption of excavator systems, which is necessary to examine the fuel efficiency improvement margin and the improvement effect. However, to effectively study the improvement of excavator efficiency, the real-time energy consumption characteristics must be examined through simulations and analyses of actual equipment-based energy consumption. Accordingly, this study establishes an energy flow-down model for the entire excavator system based on actual equipment tests. A measurement system is built to measure the required data, thereby establishing an experimental methodology for modeling each component. This paper presents an excavator system energy flow-down methodology that integrates the energy flow-down model, measurement system, and experimental methodology. This methodology was applied to dig and dump operations, and the energy consumption characteristics were analyzed. An analysis of the operating modes indicates that 59.8% of the total fuel energy was consumed in the engine system, 17% in the hydraulic system, and 23.2% in the hydraulic actuation systems. The methodology can be used to help analysis of the fuel efficiency improvement margin under various conditions.