Bradley C. Glenn

Mechatronic design and control of hybrid electric vehicles

The work in this paper presents techniques for design, development, and control of hybrid electric vehicles (HEV). Toward these ends, four issues are explored. First, the development of HEV is presented. This synopsis includes a novel definition of degree of hybridization for automotive vehicles. Second, a load-leveling vehicle operation strategy is developed. In order to accomplish the strategy, a fuzzy logic controller is proposed. Fuzzy logic control is chosen because of the need for a controller for a nonlinear, multidomain, and time-varying plant with multiple uncertainties. Third, a novel technique for system integration and component sizing is presented. Fourth, the system design and control strategy is both simulated and then implemented in an actual vehicle. The controller examined in this study increased the fuel economy of a conventional full-sized vehicle from 40 to 55.7 mi/h and increased the average efficiency over the Federal Urban Driving Schedule from 23% to 35.4%. The paper concludes with a discussion of the implications of intelligent control and mechatronic systems as they apply to automobiles.

Restoring cortical control of functional movement in a human with quadriplegia

Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic ‘neural bypass’ to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant’s forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5–C6) to the seventh cervical to first thoracic (C7–T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.

Control Design of Electrically Assisted Boosting Systems for Diesel Powertrain Applications

In this paper, we investigate the control design problem associated with the use of an electrically assisted turbo-charger (TC) for a modern Diesel engine plant. It is shown that the proposed system has the potential of improving the control bandwidth of air charge regulation relative to conventional systems. The improved control authority creates the potential for precise regulation of the fresh air fraction in the air charge. A previously developed model of a Diesel engine with variable geometry turbocharging (VGT) and Exhaust Gas Recirculation (EGR) is augmented with the model of a permanent magnet synchronous motor (PMSM) to create the model of the Turbo Electrical Assist (TEA) system. The effect of exhaust gas recirculation (EGR) on the electric power requirement of the PMSM is examined over a federal test procedure (FTP) test drive cycle. Control design is performed using the sliding mode framework.

Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

Observer design of critical states for air path flow regulation in a variable geometry turbocharger exhaust gas recirculation diesel engine

Modern automotive diesel engines rely on control strategies that must optimally manage the flows of fresh air and recirculated exhaust gas to achieve the best trade-off between torque demand and engine out emissions. An important aspect of the gas exchange regulation problem is the complex interaction between the variable geometry turbocharger (VGT) and the exhaust gas recirculation (EGR) valve and their associated flows. Control strategies that seek to optimize these flows must either have direct flow measurements or have access to the state variables that provide information on these flows. Furthermore, while the precise control of high-pressure (HP) EGR flow is essential, minimizing its usage is desirable given the engine durability concerns related to the excessive use of HP EGR, such as EGR valve coking and sticking, plugged EGR cooler, cylinder deposits, and valve deposits, to name a few. Exhaust gas recirculation may be optimally used if information on the level of inertness or leanness (oxygen content) of the exhaust gases is available. This paper presents the systematic design of observers for state variables that facilitate the design of such an optimal gas exchange control policy, thereby eliminating the need for direct sensing of the state variables for which the observer designs are proposed.

Sensorless position control of a linear voice-coil transducer using sliding mode observers

There are numerous applications where a voice coil actuator is used for position control and it is not desirable to have a physical position sensor for feedback. This paper proposes a technique for sensorless position estimation of a linear voice coil transducer using sliding mode observers. The method exploits the fact that some voice coil designs possess position-dependent force and back-emf parameters due to their geometrical properties. Using an observer structure that incorporates these position-dependent parameters of the transducer allows the coil position to be observed from a current measurement. The nonlinear model developed for the voice coil is validated and experimental results are presented and discussed. Observability is proven and the results are incorporated into a sliding mode position feedback control algorithm.