Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study

The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain and its complex structures. Hardware-In-the-Loop (HIL) simulation provides an open and convenient environment for the modeling, prototyping, testing and analyzing HEV control systems. This thesis focuses on the development of such a HIL system for the hybrid electric vehicle study. The hardware architecture of the HIL system, including dSPACE eDrive HIL simulator, MicroAutoBox II and MotoTron Engine Control Module (ECM), is introduced. Software used in the system includes dSPACE Real-Time Interface (RTI) blockset, Automotive Simulation Models (ASM), Matlab/Simulink/Stateflow, Real-time Workshop, ControlDesk Next Generation, ModelDesk and MotoHawk/MotoTune. A case study of the development of control systems for a single shaft parallel hybrid electric vehicle is presented to summarize the functionality of this HIL system.

MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES

Conventional vehicles are creating pollution problems, global warming and the extinction of high density fuels. To address these problems, automotive companies and universities are researching on hybrid electric vehicles where two different power devices are used to propel a vehicle. This research studies the development and testing of a dynamic model for Prius 2010 Hybrid Synergy Drive (HSD), a power-split device. The device was modeled and integrated with a hybrid vehicle model. To add an electric only mode for vehicle propulsion, the hybrid synergy drive was modified by adding a clutch to carrier 1. The performance of the integrated vehicle model was tested with UDDS drive cycle using rule-based control strategy. The dSPACE Hardware-In-the-Loop (HIL) simulator was used for HIL simulation test. The HIL simulation result shows that the integration of developed HSD dynamic model with a hybrid vehicle model was successful. The HSD model was able to split power and isolate engine speed from vehicle speed in hybrid mode.

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Impact of E22 on two-stroke and four-stroke snowmobiles

A push to reduce dependency on foreign energy and increase the use of renewable energy has many gas stations pumping ethanol blended fuels. Recreational engines typically have less complex fuel management systems than that of the automotive sector. This prevents the engine from being able to adapt to different ethanol concentrations. Using ethanol blended fuels in recreational engines raises several consumer concerns. Engine performance and emissions are both affected by ethanol blended fuels. This research focused on assessing the impact of E22 on two-stroke and four-stroke snowmobiles. Three snowmobiles were used for this study. A 2009 Arctic Cat Z1 Turbo with a closed-loop fuel injection system, a 2009 Yamaha Apex with an open-loop fuel injection system and a 2010 Polaris Rush with an open-loop fuel injection system were used to determine the impact of E22 on snowmobile engines. A five mode emissions test was conducted on each of the snowmobiles with E0 and E22 to determine the impact of the E22 fuel. All of the snowmobiles were left in stock form to assess the effect of E22 on snowmobiles currently on the trail. Brake specific emissions of the snowmobiles running on E22 were compared to that of the E0 fuel. Engine parameters such as exhaust gas temperature, fuel flow, and relative air to fuel ratio (λ) were also compared on all three snowmobiles. Combustion data using an AVL combustion analysis system was taken on the Polaris Rush. This was done to compare in-cylinder pressures, combustion duration, and location of 50% mass fraction burn. E22 decreased total hydrocarbons and carbon monoxide for all of the snowmobiles and increased carbon dioxide. Peak power increased for the closed-loop fuel injected Arctic Cat. A smaller increase of peak power was observed for the Polaris due to a partial ability of the fuel management system to adapt to ethanol. A decrease in peak power was observed for the open-loop fuel injected Yamaha.

MULTIDIMENSIONAL OPTIMAL DROOP CONTROL FOR WIND RESOURCES IN DC MICROGRIDS

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

A STUDY ON REGIONAL CIRCULAR ECONOMY SYSTEM AND ITS CONSTRUCTION, OPERATION AND SUGGESTION FOR SHANGHAI

The characteristics of the traditional linear economic model are high consumption, high emission and low efficiency. Economic development is still largely at the expense of the environment and requires a natural resource investment. This can realize rapid economic development but resource depletion and environmental pollution become increasingly serious. In the 1990's a new economic model, circular economics, began to enter our vision. The circular economy maximizes production and minimizes the impact of economic activities on the ecological environment through organizing the activities through the closed-loop feedback cycle of "resources - production - renewable resource". Circular economy is a better way to solve the contradictions between the economic development and resource shortages. Developing circular economy has become the major strategic initiatives to achieving sustainable development in countries all over the world. The evaluation of the development of circular economics is a necessary step for regional circular economy development. Having a quantitative evaluation of circular economy can better monitor and reveal the contradictions and problems in the process of the development of recycling economy. This thesis will: 1) Create an evaluation model framework and new types of industries and 2) Make an evaluation of the Shanghai circular economy currently to analyze the situation of Shanghai in the development of circular economy. I will then propose suggestions about the structure and development of Shanghai circular economy.

USING INDICATORS OF BIOTIC INTEGRITY FOR ASSESSMENT OF STREAM CONDITION

Multiple indices of biotic integrity and biological condition gradient models have been developed and validated to assess ecological integrity in the Laurentian Great Lakes Region. With multiple groups such as Tribal, Federal, and State agencies as well as scientists and local watershed management or river-focused volunteer groups collecting data for bioassessment it is important that we determine the comparability of data and the effectiveness of indices applied to these data for assessment of natural systems. We evaluated the applicability of macroinvertebrate and fish community indices for assessing site integrity. Site quality (i.e., habitat condition) could be classified differently depending on which index was applied. This highlights the need to better understand the metrics driving index variation as well as reference conditions for effective communication and use of indices of biotic integrity in the Upper Midwest. We found the macroinvertebrate benthic community index for the Northern Lakes and Forests Ecoregion and a coldwater fish index of biotic integrity for the Upper Midwest were most appropriate for use in the Big Manistee River watershed based on replicate sampling, ability to track trends over time and overall performance. We evaluated three sites where improper road stream crossings (culverts) were improved by replacing them with modern full-span structures using the most appropriate fish and macroinvertebrate IBIs. We used a before-after-control-impact paired series analytical design and found mixed results, with evidence of improvement in biotic integrity based on macroinvertebrate indices at some of the sites while most sites indicated no response in index score. Culvert replacements are often developed based on the potential, or the perception, that they will restore ecological integrity. As restoration practitioners, researchers and managers, we need to be transparent in our goals and objectives and monitor for those results specifically. The results of this research serve as an important model for the broader field of ecosystem restoration and support the argument that while biotic communities can respond to actions undertaken with the goal of overall restoration, practitioners should be realistic in their expectations and claims of predicted benefit, and then effectively evaluate the true impacts of the restoration activities.

MILITARY VEHICLE OPTIMIZATION AND CONTROL

It is remarkable that there are no deployed military hybrid vehicles since battlefield fuel is approximately 100 times the cost of civilian fuel. In the commercial marketplace, where fuel prices are much lower, electric hybrid vehicles have become increasingly common due to their increased fuel efficiency and the associated operating cost benefit. An absence of military hybrid vehicles is not due to a lack of investment in research and development, but rather because applying hybrid vehicle architectures to a military application has unique challenges. These challenges include inconsistent duty cycles for propulsion requirements and the absence of methods to look at vehicle energy in a holistic sense. This dissertation provides a remedy to these challenges by presenting a method to quantify the benefits of a military hybrid vehicle by regarding that vehicle as a microgrid. This innovative concept allowed for the creation of an expandable multiple input numerical optimization method that was implemented for both real-time control and system design optimization. An example of each of these implementations was presented. Optimization in the loop using this new method was compared to a traditional closed loop control system and proved to be more fuel efficient. System design optimization using this method successfully illustrated battery size optimization by iterating through various electric duty cycles. By utilizing this new multiple input numerical optimization method, a holistic view of duty cycle synthesis, vehicle energy use, and vehicle design optimization can be achieved.

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components.

REALIZATION OF A DC MICROGRID USING A HAMILTONIAN BASED CONTROLS SOLUTION

Future power grids are envisioned to be serviced by heterogeneous arrangements of renewable energy sources. Due to their stochastic nature, energy storage distribution and management are pivotal in realizing microgrids serviced heavily by renewable energy assets. Identifying the required response characteristics to meet the operational requirements of a power grid are of great importance and must be illuminated in order to discern optimal hardware topologies. Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) presents the tools to identify such characteristics. By using energy storage as actuation within the closed loop controller, the response requirements may be identified while providing a decoupled controller solution. A DC microgrid servicing a fixed RC load through source and bus level storage managed by HSSPFC was realized in hardware. A procedure was developed to calibrate the DC microgrid architecture of this work to the reduced order model used by the HSSPFC law. Storage requirements were examined through simulation and experimental testing. Bandwidth contributions between feed forward and PI components of the HSSPFC law are illuminated and suggest the need for well-known system losses to prevent the need for additional overhead in storage allocations. The following work outlines the steps taken in realizing a DC microgrid and presents design considerations for system calibration and storage requirements per the closed loop controls for future DC microgrids.