34 research outputs found
ABatRe-Sim: A Comprehensive Framework for Automated Battery Recycling Simulation
With the rapid surge in the number of on-road Electric Vehicles (EVs), the
amount of spent lithium-ion (Li-ion) batteries is also expected to explosively
grow. The spent battery packs contain valuable metal and materials that should
be recovered, recycled, and reused. However, only less than 5% of the Li-ion
batteries are currently recycled, due to a multitude of challenges in
technology, logistics and regulation. Existing battery recycling is performed
manually, which can pose a series of risks to the human operator as a
consequence of remaining high voltage and chemical hazards. Therefore, there is
a critical need to develop an automated battery recycling system. In this
paper, we present ABatRe-sim, an open-source robotic battery recycling
simulator, to facilitate the research and development in efficient and
effective battery recycling au-omation. Specifically, we develop a detailed CAD
model of the battery pack (with screws, wires, and battery modules), which is
imported into Gazebo to enable robot-object interaction in the robot operating
system (ROS) environment. It also allows the simulation of battery packs of
various aging conditions. Furthermore, perception, planning, and control
algorithms are developed to establish the benchmark to demonstrate the
interface and realize the basic functionalities for further user customization.
Discussions on the utilization and future extensions of the simulator are also
presented
Simultaneous Suspension Control and Energy Harvesting through Novel Design and Control of a New Nonlinear Energy Harvesting Shock Absorber
Simultaneous vibration control and energy harvesting of vehicle suspensions
have attracted significant research attention over the past decades. However,
existing energy harvesting shock absorbers (EHSAs) are mainly designed based on
the principle of linear resonance, thereby compromising suspension performance
for high-efficiency energy harvesting and being only responsive to narrow
bandwidth vibrations. In this paper, we propose a new EHSA design -- inerter
pendulum vibration absorber (IPVA) -- that integrates an electromagnetic rotary
EHSA with a nonlinear pendulum vibration absorber. We show that this design
simultaneously improves ride comfort and energy harvesting efficiency by
exploiting the nonlinear effects of pendulum inertia. To further improve the
performance, we develop a novel stochastic linearization model predictive
control (SL-MPC) approach in which we employ stochastic linearization to
approximate the nonlinear dynamics of EHSA that has superior accuracy compared
to standard linearization. In particular, we develop a new stochastic
linearization method with guaranteed stabilizability, which is a prerequisite
for control designs. This leads to an MPC problem that is much more
computationally efficient than the nonlinear MPC counterpart with no major
performance degradation. Extensive simulations are performed to show the
superiority of the proposed new nonlinear EHSA and to demonstrate the efficacy
of the proposed SL-MPC
Physics-Augmented Data-EnablEd Predictive Control for Eco-driving of Mixed Traffic Considering Diverse Human Behaviors
Data-driven cooperative control of connected and automated vehicles (CAVs)
has gained extensive research interest as it can utilize collected data to
generate control actions without relying on parametric system models that are
generally challenging to obtain. Existing methods mainly focused on improving
traffic safety and stability, while less emphasis has been placed on energy
efficiency in the presence of uncertainties and diversities of human-driven
vehicles (HDVs). In this paper, we employ a data-enabled predictive control
(DeePC) scheme to address the eco-driving of mixed traffic flows with diverse
behaviors of human drivers. Specifically, by incorporating the physical
relationship of the studied system and the Hankel matrix update from the
generalized behavior representation to a particular one, we develop a new
Physics-Augmented Data-EnablEd Predictive Control (PA-DeePC) approach to handle
human driver diversities. In particular, a power consumption term is added to
the DeePC cost function to reduce the holistic energy consumption of both CAVs
and HDVs. Simulation results demonstrate the effectiveness of our approach in
accurately capturing random human driver behaviors and addressing the complex
dynamics of mixed traffic flows, while ensuring driving safety and traffic
efficiency. Furthermore, the proposed optimization framework achieves
substantial reductions in energy consumption, i.e., average reductions of 4.83%
and 9.16% when compared to the benchmark algorithms
Challenges and Opportunities for Second-life Batteries: A Review of Key Technologies and Economy
Due to the increasing volume of Electric Vehicles in automotive markets and
the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale
retirement of LIBs is imminent. The battery packs retired from Electric
Vehicles still own 70%-80% of the initial capacity, thus having the potential
to be utilized in scenarios with lower energy and power requirements to
maximize the value of LIBs. However, spent batteries are commonly less reliable
than fresh batteries due to their degraded performance, thereby necessitating a
comprehensive assessment from safety and economic perspectives before further
utilization. To this end, this paper reviews the key technological and economic
aspects of second-life batteries (SLBs). Firstly, we introduce various
degradation models for first-life batteries and identify an opportunity to
combine physics-based theories with data-driven methods to establish
explainable models with physical laws that can be generalized. However,
degradation models specifically tailored to SLBs are currently absent.
Therefore, we analyze the applicability of existing battery degradation models
developed for first-life batteries in SLB applications. Secondly, we
investigate fast screening and regrouping techniques and discuss the regrouping
standards for the first time to guide the classification procedure and enhance
the performance and safety of SLBs. Thirdly, we scrutinize the economic
analysis of SLBs and summarize the potentially profitable applications.
Finally, we comprehensively examine and compare power electronics technologies
that can substantially improve the performance of SLBs, including
high-efficiency energy transformation technologies, active equalization
technologies, and technologies to improve reliability and safety
Infrared Plasmonic Sensing with Anisotropic Two-Dimensional Material Borophene
Borophene, a new member of the two-dimensional material family, has been found to support surface plasmon polaritons in visible and infrared regimes, which can be integrated into various optoelectronic and nanophotonic devices. To further explore the potential plasmonic applications of borophene, we propose an infrared plasmonic sensor based on the borophene ribbon array. The nanostructured borophene can support localized surface plasmon resonances, which can sense the local refractive index of the environment via spectral response. By analytical and numerical calculation, we investigate the influences of geometric as well as material parameters on the sensing performance of the proposed sensor in detail. The results show how to tune and optimize the sensitivity and figure of merit of the proposed structure and reveal that the borophene sensor possesses comparable sensing performance with conventional plasmonic sensors. This work provides the route to design a borophene plasmonic sensor with high performance and can be applied in next-generation point-of-care diagnostic devices
A New Way of Rice Breeding: Polyploid Rice Breeding
Polyploid rice, first discovered by Japanese scientist Eiiti Nakamori in 1933, has a history of nearly 90 years. In the following years, polyploid rice studies have mainly focused on innovations in breeding theory, induction technology and the creation of new germplasm, the analysis of agronomic traits and nutritional components, the study of gametophyte development and reproduction characteristics, DNA methylation modification and gene expression regulation, distant hybridization and utilization among subspecies, species and genomes. In recent years, PMeS lines and neo-tetraploid rice lines with stable high seed setting rate characteristics have been successively selected, breaking through the bottleneck of low seed setting rate of polyploid rice. Following, a series of theoretical and applied studies on high seed setting rate tetraploid rice were carried out. This has pushed research on polyploid rice to a new stage, opening new prospects for polyploid rice breeding