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Braking energy recovery (BER) aims to recover the vehicle's kinetic energy by coordinating the motor and mechanical braking torque to extend the driving range of the electric vehicle (EV). To achieve this goal, the motor/generator mode requires frequent switching and prolonged operation during driving. In this case, the motor temperature will unavoidably rise, potentially triggering motor thermal protection (MTP). Activating MTP increases the risk of motor component failure, and the EV typically disables the BER function. Thus, maximizing BER while reducing the risk of motor overheating is a challenging problem. To address this issue, this article proposes a predictive BER strategy with MTP using the non-smooth Pontryagin Minimum Principle (NSPMP) for EVs. Firstly, a Markov long short-term memory (MLSTM) model is designed to obtain future velocity information. Secondly, the BER problem with MTP in the studied EV is embedded in a model predictive control (MPC) framework. Then, under the MPC framework, the NSPMP strategy is proposed to resolve the problem of MTP. Finally, the performance of the proposed strategy is verified through simulation and a hardware-in-loop test. The results show that in two real-world driving cycles, compared to the rule-based strategy, the proposed strategy reduced power consumption by 1.24% and 0.96%, respectively, and effectively limited motor temperature. Additionally, under global cycle conditions, this strategy demonstrated better MTP control performance compared to other benchmark strategies. [ABSTRACT FROM AUTHOR]

The affinity interactions between boronic acids and sugars have been successfully exploited in many fields, such as the sensing of saccharides, selective enrichment of glycoconjugates, and drug delivery. However, despite multiple techniques having been adopted to investigate the reaction of boronate affinity, the pathway of boronate esters formation under aqueous conditions remains controversial. We report a MALDI-MS approach to investigate the interactions between phenylboronic acid and monosaccharides in neutral aqueous solution by using polylevodopa as an innovative substrate instead of conventional matrix. A series of unusual tri-benzeneboronic esters were then revealed. The mass spectrometry data indicate that they bear a dibenzenepyroboronate cyclic ester moiety with seven-membered ring or eight-membered ring. With the aid of theoretical computations, their most likely geometrical structures are elucidated, and these tri-benzeneboronic esters are proposed to be formed via a boroxine binding monosaccharide pathway. This work provides more insight into the mechanism of boronate affinity interaction between boronic acid and sugars and proves the developed MALDI-MS approach is promising for studying interactions between small molecules. [ABSTRACT FROM AUTHOR]

Power flow optimization control, which governs the energy flow among engine, battery, and motor, plays a very important role in plug-in hybrid electric vehicles (PHEVs). Its performance directly affects the fuel economy of PHEVs. For the purpose of improving fuel economy, the electric system including battery and motor will be frequently scheduled, which would affect battery life. Therefore, a multi-objective optimization mechanism taking fuel economy and battery life into account is necessary, which is also a research focus in field of hybrid vehicles. Motivated by this issue, this paper proposes a multi-objective power flow optimization control strategy for a power split PHEV using game theory. Firstly, since the demand power of driver which is necessary for the power flow optimization control, cannot be known in advance, the demand power of driver can be modelled using a Markov chain to obtain predicted demand power. Secondly, based on the predicted demand power, the multi-objective optimization control problem is transformed into a game problem. A novel non-cooperative game model between engine and battery is established, and the benefit function with fuel economy and battery life as the optimization objective is proposed. Thirdly, under the premise of satisfying various constraints, the participants of the above game maximize their own benefit function to obtain the Nash equilibrium, which comprises of optimal power split scheme. Finally, the proposed strategy is verified compared with two baseline strategies, and results show that the proposed strategy can reduce equivalent fuel consumption by about 15% compared with baseline strategy 1, and achieve similar fuel economy while greatly extend battery life simultaneously compared with baseline strategy 2. [ABSTRACT FROM AUTHOR]

Improvements in coating deposition technology enable the mass production of high-quality diamond-like carbon (DLC) coatings at an industrial scale and also increase their use in lubricated contacts. However, the understanding of the interactions of different lubricant additives with this material is not yet fully developed. This study focuses on several fundamental aspects of the tungsten-doped DLC coating (denoted as WDLC) behaviour under boundary lubrication conditions with model lubricants. The effect of lubricant additives on the coating structure change is discussed in terms of carbon structure and the tungsten dopant. Electron energy-loss spectroscopy, XPS and Raman spectroscopy characterization for the upper carbon layers indicate that the WDLC coating interacts chemically with selected lubricant additives. The study provides information on both coating and additive optimization under boundary lubrication. [ABSTRACT FROM AUTHOR]