In order to monitor the running state of fuel cell and prolong its service life, fault diagnosis technology has been widely researched. The fuel cell equivalent circuit model (ECM) can easily characterize the water content and membrane drying of the cells which has attracted the attention of scholars. Usually ECM is obtained by electrochemical impedance spectroscopy (EIS), and uses an electronic load for impedance excitation test, then achieves parameter identification through algorithms for fault diagnosis. This paper proposes a novel fuel cell ECM model parameter identification method by constructing a new combined network that the fuel cell ECM is included. It doesn’t require an electronic load to provide an excitation, meanwhile it relies on the DC/DC converter’s input voltage and inductor current, without voltage and current sensors on the fuel cell side. It uses the least square method to identify this new combined network’s parameter. This method reduces the cost of system components and achieves a good test performance.
An $r$-uniform hypergraph $H$ is \emph{semi-algebraic} of complexity $\mathbf{t}=(d,D,m)$ if the vertices of $H$ correspond to points in $\mathbb{R}^{d}$, and the edges of $H$ are determined by the sign-pattern of $m$ degree-$D$ polynomials. Semi-algebraic hypergraphs of bounded complexity provide a general framework for studying geometrically defined hypergraphs. The much-studied \emph{semi-algebraic Ramsey number} $R_{r}^{\mathbf{t}}(s,n)$ denotes the smallest $N$ such that every $r$-uniform semi-algebraic hypergraph of complexity $\mathbf{t}$ on $N$ vertices contains either a clique of size $s$, or an independent set of size $n$. Conlon, Fox, Pach, Sudakov and Suk proved that $R_{r}^{\mathbf{t}}(n,n)
The algorithm and complexity of approximating the permanent of a matrix is an extensively studied topic. Recently, its connection with quantum supremacy and more specifically BosonSampling draws a special attention to the average-case approximation problem of the permanent of random matrices with zero or small mean value for each entry. Eldar and Mehraban (FOCS 2018) gave a quasi-polynomial time algorithm for random matrices with mean at least 1/ polyloglog(n). In this paper, we improve the result by designing a deterministic quasi-polynomial time algorithm and a PTAS for random matrices with mean at least 1/ polylog(n). We note that if it can be further improved to 1/ poly(n), it will disprove a central conjecture for quantum supremacy.Our algorithm is also much simpler and has a better and flexible trade-off for running time. The running time can be quasi-polynomial in both n and 1/ε, or PTAS (polynomial in n but exponential in 1/ε), where ε is the approximation parameter.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.