Integrated Steering and Braking Control System for Collision Avoidance by Using Virtual Repulsive Force Field Method

Advanced Driver Assistance Systems (ADAS) and autonomous driving systems are being enhanced to deal with various types of collision avoidance use-case scenarios. To handle those complicated scenarios, a unified two-dimensional planar motion control methodology assuming virtual repulsive force from obstacles is introduced, which is physically interpretable and comprehensible. The direction and magnitude of virtual repulsive force are determined considering the orientation of obstacle surface planes and the friction limit between tires and road surface respectively. Applying the concept of virtual repulsive force field, the collision avoidance path can be derived from geometrical relationship and the control activation points can be obtained as algebraic solutions. By using a simple particle mass model, the formulation for path and control activation point is described. The simulation is conducted against not only in the case of a straight roadway but also in the case of a curve roadway. By designing feedforward and feedback controllers based on a two-wheel vehicle dynamics model, the effectiveness of the proposed method is verified and the feasibility of controller implementation for actual vehicle is also investigated.

An Economic Model Predictive Control Approach for Wind Power Smoothing and Tower Load Mitigation

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.

Integrative Modeling Platform for Design and Control of an Adaptive Wind Turbine Blade

A platform for the engineering design, performance, and control of an adaptive wind turbine blade is presented. This environment includes a simulation model, integrative design tool, and control framework. The authors are currently developing a novel blade with an adaptive twist angle distribution (TAD). The TAD influences the aerodynamic loads and thus, system dynamics. The modeling platform facilitates the use of an integrative design tool that establishes the TAD in relation to wind speed. The outcome of this design enables the transformation of the TAD during operation. Still, a robust control method is required to realize the benefits of the adaptive TAD. Moreover, simulation of the TAD is computationally expensive. It also requires a unique approach for both partial and full-load operation. A framework is currently being developed to relate the TAD to the wind turbine and its components. Understanding the relationship between the TAD and the dynamic system is crucial in the establishment of real-time control. This capability is necessary to improve wind capture and reduce system loads. In the current state of development, the platform is capable of maximizing wind capture during partial-load operation. However, the control tasks related to Region 3 and load mitigation are more complex. Our framework will require high-fidelity modeling and reduced-order models that support real-time control. The paper outlines the components of this framework that is being developed. The proposed platform will facilitate expansion and the use of these required modeling techniques. A case study of a 20 kW system is presented based upon the partial-load operation. The study demonstrates how the platform is used to design and control the blade. A low-dimensional aerodynamic model characterizes the blade performance. This interacts with the simulation model to predict the power production. The design tool establishes actuator locations and stiffness properties required for the blade shape to achieve a range of TAD configurations. A supervisory control model is implemented and used to demonstrate how the simulation model blade performs in the case study.

Modeling Li-Ion Battery Thermal Runaway Using a Three Section Thermal Model

This paper presents a model describing lithium-ion battery thermal runaway triggered by an internal short. The model predicts temperature and heat generation from the internal short circuit and side reactions using a three-section model. The three sections correspond to the core, middle, and surface layers. At each layer, the temperature-dependent heat release and progression of the three major side reactions are modeled. A thermal runaway test was conducted on a 4.5 Ah nickel manganese cobalt oxide pouch cell, and the temperature measurements are used for model validation. The proposed reduced order model based on three sections can balance the computational speed with the model complexity required to predict the fast core temperature evolution and slower surface temperature growth. The model shows good agreement with the experimental data, and it will be further improved with formal tuning in a follow-up effort to enable early detection of thermal runway induced by internal short.

Simultaneous Optimization of Configuration and Control for a Passive SCR System

The configuration and control of aftertreatment systems have a significant impact on their functionalities and emission control performance. The traditional aftertreatment system configurations, i.e., connections from one aftertreatment subsystem to another subsystem in series, are simple but generally do not yield the optimal aftertreatment system performance. New aftertreatment configurations, in conjunction with new engine and aftertreatment control, can significantly improve engine efficiency and emission reduction performance. However, new configuration design requires human intuition and in-depth knowledge of engine and aftertreatment system design and control. The purpose of this study is to develop a general systematic and computationally-efficient method which enables automated and simultaneous optimization of passive selective catalytic reduction (SCR) system architectures and the associated non-uniform cylinder-to-cylinder combustion (NUCCC) controls based on a newly proposed highly reconfigurable passive SCR model structure and integer partition theory. The proposed method is general enough to account for passive SCR systems with two or more TWC stages. We demonstrate through this case study that the optimized passive SCR configuration, in conjunction with the optimized NUCCC control, can reduce the NH3 specific fuel consumption by up to 21.90%.

Model Predictive Control of a Pumped Two-Phase Cooling System With Microchannel Heat Exchangers

Two-phase cooling systems provide a viable technology for high–heat flux rejection in electronic systems. They provide high cooling capacity and uniform surface temperature. However, a major restriction of their application is the critical heat flux condition (CHF). This work presents model predictive control (MPC) design for CHF avoidance in two-phase pump driven cooling systems. The system under study includes multiple microchannel heat exchangers in series. The MPC controller performance is compared to the performance of a baseline PI controller. Simulation results show that while both controllers are able to maintain the two-phase cooling system below CHF, MPC has significant reduction in power consumption compared to the baseline controller.

Optimization of Mode Switching Timing Control for a Lean-Burn Gasoline Engine With a Prototype Passive SCR System

Passive selective catalytic reduction (SCR) has emerged as a promising NOx reduction technology for highly-efficient lean-burn gasoline engines to meet stringent NOx emission regulation in a cost-effective manner. In this study, a prototype passive SCR which includes an upstream three-way catalyst (TWC) with added NOx storage component, and a downstream urealess SCR catalyst, was investigated. Engine experiments were conducted to investigate and quantify the dynamic NOx storage/release behaviors as well as dynamic NH3 generation behavior on the new TWC with added NOx storage component. Then, the lean/rich mode-switching timing control was optimized to minimize the fuel penalty associated with passive SCR operation. Simulation results show that, compared to the baseline mode-switching timing control, the optimized control can reduce the passive SCR-related fuel penalty by 6.7%. Such an optimized mode-switching timing control strategy is rather instrumental in realizing significant fuel efficiency benefits for lean-burn gasoline engines coupled with cost-effective passive SCR systems.

A Control-Oriented Reaction-Based SI Engine Combustion Model

This paper proposes a control-oriented chemical reaction-based two-zone combustion model designed to accurately describe the combustion process and thermal performance for spark-ignition engines. The combustion chamber is assumed to be divided into two zones: reaction and unburned zones, where the chemical reaction takes place in the reaction zone and the unburned zone contains all the unburned mixture. In contrast to the empirical pre-determined Wiebe-function-based combustion model, an ideal two-step chemical reaction mechanism is used to reliably model the detailed combustion process such as mass-fraction-burned (MFB) and rate of heat release. The interaction between two zones includes mass and heat transfer at the zone interface to have a smooth combustion process. This control-oriented model is extensively calibrated based on the experimental data to demonstrate its capability of predicting the combustion process and thermodynamic states of the in-cylinder mixture.

Optimization of Energy-Efficient Speed Profile for Electrified Vehicles

This paper presents a study of energy-efficient operation of vehicles with electrified powertrains leveraging route information, such as road grades, to adjust the speed trajectory. First, Pontryagin’s Maximum Principle (PMP) is applied to derive necessary conditions and to determine the possible operating modes. The analysis shows that only 5 modes are required to achieve minimum energy consumption; full propulsion, cruising, coasting, full regeneration, and full regeneration with conventional braking. The minimum energy consumption problem is reformulated and solved in the distance domain using Dynamic Programming to optimize speed profiles. A case study is shown for a light weight military robot including road grades. For this system, a tradeoff between energy consumption and trip time was found. The optimal cycle uses 20% less energy for the same trip duration, or could reduce the travel time by 14% with the same energy consumption compared to the baseline operation.

Towards Automated Bicycles: Achieving Self-Balance Using Steering Control

In recent years, researchers from both academia and industry have worked on connected and automated vehicles and they have made great progress toward bringing them into reality. Compared to automated cars, bicycles are more affordable to daily commuters, as well as more environmentally friendly. When comparing the risk posed by autonomous vehicles to pedestrians and motorists, automated bicycles are much safer than autonomous cars, which also allows potential applications in smart cities, rehabilitation, and exercise. The biggest challenge in automating bicycles is the inherent problem of staying balanced. This paper presents a modified electric bicycle to allow real-time monitoring of the roll angles and motor-assisted steering. Stable and robust steering controllers for bicycle are designed and implemented to achieve self-balance at different forward speeds. Tests at different speeds have been conducted to verify the effectiveness of hardware development and controller design. The preliminary design using a control moment gyroscope (CMG) to achieve self-balancing at lower speeds are also presented in this work. This work can serve as a solid foundation for future study of human-robot interaction and autonomous driving.