A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur

Accurate prediction of range of an electric vehicle (EV) is a significant issue and a key market qualifier. EV range forecasting can be made practicable through the application of advanced modelling and estimation techniques. Battery modelling and state-of-charge estimation methods play a vital role in this area. In addition, battery modelling is essential for safe charging/discharging and optimal usage of batteries. Much existing work has been carried out on incumbent Lithium-ion (Li-ion) technologies, but these are reaching their theoretical limits and modern research is also exploring promising next-generation technologies such as Lithium–Sulphur (Li–S). This study reviews and discusses various battery modelling approaches including mathematical models, electrochemical models and electrical equivalent circuit models. After a general survey, the study explores the specific application of battery models in EV battery management systems, where models may have low fidelity to be fast enough to run in real-time applications. Two main categories are considered: reduced-order electrochemical models and equivalent circuit models. The particular challenges associated with Li–S batteries are explored, and it is concluded that the state-of-the-art in battery modelling is not sufficient for this chemistry, and new modelling approaches are needed

A physical model suggests that hip-localized balance sense in birds improves state estimation in perching: implications for bipedal robots

In addition to a vestibular system, birds uniquely have a balance-sensing organ within the pelvis, called the lumbosacral organ (LSO). The LSO is well developed in terrestrial birds, possibly to facilitate balance control in perching and terrestrial locomotion. No previous studies have quantified the functional benefits of the LSO for balance. We suggest two main benefits of hip-localized balance sense: reduced sensorimotor delay and improved estimation of foot-ground acceleration. We used system identification to test the hypothesis that hip-localized balance sense improves estimates of foot acceleration compared to a head-localized sense, due to closer proximity to the feet. We built a physical model of a standing guinea fowl perched on a platform, and used 3D accelerometers at the hip and head to replicate balance sense by the LSO and vestibular systems. The horizontal platform was attached to the end effector of a 6 DOF robotic arm, allowing us to apply perturbations to the platform analogous to motions of a compliant branch. We also compared state estimation between models with low and high neck stiffness. Cross-correlations revealed that foot-to-hip sensing delays were shorter than foot-to-head, as expected. We used multi-variable output error state-space (MOESP) system identification to estimate foot-ground acceleration as a function of hip- and head-localized sensing, individually and combined. Hip-localized sensors alone provided the best state estimates, which were not improved when fused with head-localized sensors. However, estimates from head-localized sensors improved with higher neck stiffness. Our findings support the hypothesis that hip-localized balance sense improves the speed and accuracy of foot state estimation compared to head-localized sense. The findings also suggest a role of neck muscles for active sensing for balance control: increased neck stiffness through muscle co-contraction can improve the utility of vestibular signals. Our engineering approach provides, to our knowledge, the first quantitative evidence for functional benefits of the LSO balance sense in birds. The findings support notions of control modularity in birds, with preferential vestibular sense for head stability and gaze, and LSO for body balance control,respectively. The findings also suggest advantages for distributed and active sensing for agile locomotion in compliant bipedal robots

Weak Values are Interference Phenomena

Weak values arise experimentally as conditioned averages of weak (noisy) observable measurements that minimally disturb an initial quantum state, and also as dynamical variables for reduced quantum state evolution even in the absence of measurement. These averages can exceed the eigenvalue range of the observable ostensibly being estimated, which has prompted considerable debate regarding their interpretation. Classical conditioned averages of noisy signals only show such anomalies if the quantity being measured is also disturbed prior to conditioning. This fact has recently been rediscovered, along with the question whether anomalous weak values are merely classical disturbance effects. Here we carefully review the role of the weak value as both a conditioned observable estimation and a dynamical variable, and clarify why classical disturbance models will be insufficient to explain the weak value unless they can also simulate other quantum interference phenomena.Comment: 16 pages, 4 figures, lots of references; v2 considerably expanded for pedagogical clarity; v3 minor typos fixe

The stochastic quasi-steady-state assumption: Reducing the model but not the noise

Highly reactive species at small copy numbers play an important role in many biological reaction networks. We have described previously how these species can be removed from reaction networks using stochastic quasi-steady-state singular perturbation analysis (sQSPA). In this paper we apply sQSPA to three published biological models: the pap operon regulation, a biochemical oscillator, and an intracellular viral infection. These examples demonstrate three different potential benefits of sQSPA. First, rare state probabilities can be accurately estimated from simulation. Second, the method typically results in fewer and better scaled parameters that can be more readily estimated from experiments. Finally, the simulation time can be significantly reduced without sacrificing the accuracy of the solution

The estimation of a preference-based measure of health from the SF-36

This paper reports on the findings of a study to derive a preference-based measure of health from the SF-36 for use in economic evaluation. The SF-36 was revised into a six-dimensional health state classification called the SF-6D. A sample of 249 states defined by the SF-6D have been valued by a representative sample of 611 members of the UK general population, using standard gamble. Models are estimated for predicting health state valuations for all 18,000 states defined by the SF-6D. The econometric modelling had to cope with the hierarchical nature of the data and its skewed distribution. The recommended models have produced significant coefficients for levels of the SF-6D, which are robust across model specification. However, there are concerns with some inconsistent estimates and over prediction of the value of the poorest health states. These problems must be weighed against the rich descriptive ability of the SF-6D, and the potential application of these models to existing and future SF-36 data set

Determinants of spreads on sovereign bank loans: the role of credit history

This paper is an empirical investigation into the role of credit history in determining the spread on sovereign bank loans. It employs an error-in-variables approach used in rationalexpectations-macro-econometrics to set up a structural model that links sovereign loan spreads to realized repayment behavior. Unlike the existing empirical literature, its instrumental variables method allows for distinguishing a direct influence of past repayment problems (a “pure reputation ” effect) from one that goes through increased default probabilities. Using developing country data from the period 1973-1981 and constructing continuous variables for credit history, we find that past default is a significant determinant of the spread, even after including country fixed effects. Moreover, its reduced-form effect is very similar to its structural form effect, indicating that most of the influence of past repayment problems is through the reputation channel. Overall, reserves to imports, past and predicted future default are substantial determinants of sovereign bank loan spreads

Estimating union wage effects in Great Britain during 1991-2003

Using a dynamic model of unionism and wage determination we find that the unobserved factors that influence union membership also affect wages. The estimates suggest that UK trade unions still play a non-negligible, albeit diminishing, role in wage formation. It appears that the greater impact of un observables in determining individual union propensity concerning the second period under analysis, versus past unionisation experience, implies that those remaining in unions during (1997-2002) gain most from their sorting decision. The significant contribution of unobserved heterogeneity renders the total union wage differential highly variable across individuals. The endogeneity correction procedure employed yields a discernible pattern of the estimated union wage effect relative to OLS and Fixed effects. This is in line with Robinson (1989a) and Vella and Verbeek (1998) and refutes the pessimistic conclusions reached by Freeman and Medoff (1982) and Lewis (1986) that endogeneity correction methodologies do not contribute to our understanding of the union wage effect puzzle