This paper presents a flexible solid-state supercapacitor of high energy density. The electrodes of the supercapacitor are made of porous and absorbent cotton paper coated with single-wall carbon nanotubes. To ensure all solid-state configuration, a solid-state polymer-based electrolyte (poly (vinyl alcohol)/phosphoric acid) is used. The as-fabricated supercapacitor can be charged to over 3 V. It has high specific capacitance and high energy density of 115.8301 F/g carbon and 48.8587 Wh/kg carbon. Its performance is comparable to that of commercial supercapacitors, which need to utilize liquid electrolytes. Flexible solid-state supercapacitors offer several significant advantages for use in hybrid electric vehicles.

This paper develops a new high-gain observer design method for nonlinear systems that has a lower gain compared to the standard high-gain observer. This new observer, called HG/LMI observer is obtained by combining the standard high gain methodology with the LMI-based observer design technique. Through analytical developments, the paper shows how the new observer provides lower gains, shows how it applies to systems with multi nonlinear functions and analyzes performance in the presence of measurement noise and/or delayed output measurements. A numerical example is given to illustrate the increasing advantage of the new HG/LMI observer with increase in the observer's "compromise index". Finally, the applicability and performance of the observer is demonstrated for a real-world application consisting of a train's magnetic levitation system.

This paper focuses on the development and use of a nonlinear observer for tracking of vehicle motion trajectories while using a radar sensor. Previous results on vehicle tracking have typically used an interacting multiple model filter that needs different models for different modes of vehicle motion. This paper uses a single nonlinear vehicle model that can be used for all modes of vehicle motion. Previous nonlinear observer design results from the literature do not work for the nonlinear system under consideration due to the wide range of operating conditions that need to be accommodated. Hence, a new nonlinear observer design technique that utilizes better bounds on the coupled nonlinear functions in the dynamics is developed. The exponential stability of the observer is established using Lyapunov techniques. The observer design with the developed technique is then implemented in both simulations and experiments. Experimental results show that the observer can simultaneously and accurately estimate longitudinal position, lateral position, and velocity and orientation variables for the vehicle from radar measurements. Results are presented both for tracking of vehicle maneuvers on highways and of maneuvers on urban roads at traffic intersections where turns and significant changes in vehicle orientation can occur.

This paper focuses on the detection of cyber-attacks on a wireless communication channel and simultaneous radar sensor health monitoring for a connected vehicle. A semi-autonomous adaptive cruise control (SA-ACC) vehicle is considered which has wireless communication with its immediately preceding vehicle in the same lane. The wireless connectivity enables the vehicle to operate at small time-gap distances without creating string instability. However, the reliability of the wireless connectivity is critical for ensuring safe vehicle operation. The presence of two unknown inputs related to both sensor failure and cyber-attack seemingly poses a difficult estimation challenge which is addressed in this paper. The dynamic system is first represented in descriptor system form. An observer with estimation error dynamics decoupled from the cyber-attack signal is developed. The performance of the observer is first extensively evaluated in simulations. The estimation system is able to detect either a fault in the radar or a cyber-attack. Further, the proposed control strategy achieves resilient adaptive cruise control system operation by switching to larger time-gaps and a non-connected controller when a cyber-attack is detected. Finally, experimental data from a real vehicle on the I-94 Highway in Minneapolis, MN, USA is also used to evaluate the performance of the proposed algorithms. The fundamental estimation algorithm developed herein can be extended in the future to enable cyber-attack detection in more complex connected vehicle architectures.

This article focuses on state-of-charge (SoC) estimation for a lithium-ion battery modeled using a recently developed nonlinear double-capacitor representation that has been shown to be highly accurate. The measurement equation of the model has two nonlinear functions, one of them being significant hysteresis in voltage as a function of the SoC. The hysteresis term is modeled using a physically intuitive modified Preisach representation consisting of a series of hysterons which get switched on or off to produce the hysteresis phenomenon. The proposed model for the hysteresis term is not differentiable but is Lipschitz bounded. A custom nonlinear observer is designed for this class of nonlinear systems using Lyapunov analysis to guarantee asymptotic stability. The observer design procedure consists of satisfying a linear matrix inequality on a set of vertices of a convex function. The developed observer is evaluated using experimental battery data. Experimental data is also used to determine the weights of the hysterons in the data-based modified Preisach model. The nonlinear observer performs well, yielding accurate SoC estimates in the presence of hysteresis. The nonlinear observer is also compared with the extended Kalman filter and the unscented Kalman filter, and is seen to provide superior performance for the same application due to its guaranteed global convergence properties. A broad technical contribution of this article is the development of an observer design method to handle the presence of hysteresis in nonlinear systems.