The operation of a proton exchange membrane fuel cell (PEMFC) is greatly affected by temperature. Reliable thermal management of fuel cells can improve the life, efficiency, and power output of fuel cells. The model established in this paper is based on the inner layer of the fuel cell, and through the analysis of the heat change and material flow between layers, the simulink model can reflect the temperature change of the end plate, the bipolar plate, and the membrane electrode assembly (MEA) plate. In terms of the thermal management control strategy, the deviation and deviation rate between the MEA plate’s temperature and the target temperature are taken as input, and the fuzzy PID (proportional integral differential) controller is used to control the cooling water flow, to achieve a cooling effect. Due to the low efficiency and instability of a haploid genetic algorithm (GA) in solving dynamic optimization problems, a diploid genetic algorithm to optimize the membership function of the controller, and improve the adaptability of the control system, was designed. The simulation results show that compared with the haploid genetic algorithm, the optimal results of 100 iterations of the fuzzy PID control strategy reduce by 27.9%. Compared with the haploid genetic algorithm and fuzzy PID control, the MEA layer temperature, under the control of a diploid genetic algorithm, is reduced by 18% and 28%, respectively, and the minimum temperature difference of the reactor is 2.28 K.

As one of the important components of intelligent warehousing logistics, Automated Guided Vehicles (AGVs) have greatly improved the efficiency of warehousing operations. AGVs are responsible for the delivery of goods in warehousing and logistics, and it is extremely important to maintain a stable running state. In this paper, an AGV in-situ steering dynamic model is established according to the actual size, and the center deviation phenomenon during AGV steering is theoretically analyzed to obtain the parameters that affect the AGV’s in-situ steering stability. Secondly, the dynamic simulation method is used to analyze the law of the stability of the AGV in-situ steering parameters to verify the correctness of the theoretical derivation equation. According to the analysis results, the motion parameters related to AGV in-situ steering are analyzed, and a reasonable design scheme is given. Based on the optimized fork-type AGV, the AGV in-situ steering control strategy is studied, and the adaptive fuzzy PID control algorithm is used to construct the fork-type AGV steering control system. Then the software and hardware design of the AGV steering control system is carried out. The optimized fork-type AGV has been turned to work stably after commissioning, meeting the actual work requirements.

The three dimensional thermal model of a forced air-cooling battery thermal management system (BTMS) using aluminium foam heat sink (AFHS) is established, and the effects of porosity, pore density, and mass flow rate on the thermal and flow performance are discussed numerically from the aspects of pressure drop and temperature control effectiveness. The results reveal that an AFHS can markedly reduce the battery temperature compared with the BTMS without AFHS, but it also causes huge pressure loss and increases the temperature difference between the upstream and downstream of the battery. Reducing the porosity of aluminium foam reduces the battery’s average temperature, but increases the temperature difference. The increase of pore density leads to the increase of pressure drop, but has little effect on the battery temperature. Based on this, a study of the gradient porosity of the AFHS is carried out, and the thermal and flow performance are compared with the homogeneous AFHS. The results show that the AFHS with porosity-increasing gradient pattern (PIGP) in the direction perpendicular to flow reduces the pressure loss and improves flow performance. The AFHS with a porosity-decreasing gradient pattern (PDGP) in the flow direction has no obvious effect on the flow characteristics, but it can reduce the temperature difference of the battery. The direction of gradient porosity can be selected according to need. In addition, due to the energy absorption characteristics of aluminium foam, AFHS can improve the crashworthiness of the battery pack. Therefore, AFHS has great potential in air-cooled BTM.

Real-time monitoring of the battery thermal status is important to ensure the effectiveness of battery thermal management system (BTMS), which can effectively avoid thermal runaway. In the study of BTMS, driver behavior is one of the factors affecting the performance of the battery thermal status, and it is often neglected in battery temperature studies. Therefore, it is necessary to predict the dynamic heat generation of the battery in actual driving cycles. In this work, a thermal equivalent circuit model (TECM) and an artificial neural network (ANN) thermal model based on the driving data, which can predict the thermal behavior of the battery in real-world driving cycles, are proposed and established by MATLAB/Simulink tool. Driving behaviors analysis of different drivers are simulated by PI control as input, and battery temperature is used as output response. The results show that aggressive driving behavior leads to an increase in battery temperature of nearly 1.2 K per second, and the average prediction error of TECM model and ANN model is 0.13 K and 0.11 K, respectively. This indicates that both models can accurately estimate the real-time battery temperature. However, the computational speed of the ANN thermal model is only 0.2 s, which is more efficient for battery thermal management.

Driving style has a significant effect on the operating economy of fuel cell buses (FCBs). To reduce hydrogen consumption and prolong the fuel cell life of FCBs, this paper proposes an online adaptive equivalent consumption minimum strategy (A-ECMS) based on driving style recognition. Firstly, driving data from various drivers is collected, and a standard driving cycle is created. Neural networks are then used to identify driving conditions, and three fuzzy logic recognizers are developed to identify driving styles for different driving conditions. The driving style factor is associated with the equivalent factor using an optimization algorithm that incorporates hydrogen consumption cost and fuel cell degradation cost into the objective function. Simulation results demonstrate that the proposed A-ECMS can reduce equivalent hydrogen consumption, prolong fuel cell life, and result in a 6.2% reduction in total operating cost compared to the traditional method.

Batteries are widely used in our lives, but the inevitable inconsistencies in series-connected battery packs will seriously impact their energy utilization, cycle life and even jeopardize their safety in use. This paper proposes a balancing topology structure combining Buck-Boost circuit and switch array to reduce this inconsistency. This structure can realize multi-cell-to-multi-cell (MC2MC) battery balancing by controlling the switch array and having a fast balancing speed, easy expansion and few magnetic components. Then, the operation principle of the proposed balancing topology is analyzed, and the simulation model is verified. In addition, the effects of switching frequency and voltage difference on the equalization effect are further analyzed. The results show that the higher the switching frequency, the lower the time efficiency, but the higher the energy efficiency. The voltage difference significantly impacts the duty cycle, so it is absolutely necessary to introduce a variable duty cycle in the multi-cell-to-multi-cell equalization. Finally, eight series batteries are selected for simulation verification. The simulation results show that, compared with any-cell-to-any-cell (AC2AC) equalization, the time efficiency of multi-cell-to-multi-cell equalization is improved considerably, the energy efficiency is improved slightly, and the variance of the completed equalization is reduced, demonstrating the excellent performance of multi-cell-to-multi-cell equalization.