In the domain of Battery Management System (BMS) research, the precise acquisition and estimation of internal temperature distribution within lithium-ion cells is a significant challenge. The commercial viability precludes the use of internal temperature sensors, and existing methodologies for online estimation of internal temperatures under various electrical loads are constrained by computational limitations and model accuracy. This study presents a layered electro-thermal equivalent circuit model (LETECM), developed by integrating a layered second-order fractional equivalent circuit model with a layered thermal equivalent circuit model. A lithium-ion battery divided into three layers was employed to illustrate the development of this LETECM. The model’s precision was validated against a 3D Newman Finite Element Model (3DNFEM), constructed using actual battery parameters. Given that the thermal gradient inside the battery is usually more pronounced under high load conditions, a 10C direct current discharge for 60 s followed by a rest period of 240 s was adopted as the test condition in the simulation. The results indicate that at the end of the DC discharge, the temperature difference between the inner layer and the surface of the battery was the largest and the maximum temperature difference predicted by the LETECM was 3.58 °C, while the 3DNFEM exhibited a temperature difference of 3.74 °C. The trends in each layer temperature and battery surface temperature obtained by the two models are highly consistent. The proposed model offers computational efficiency and maintains notable accuracy, suggesting its potential integration into BMS for real-time online applications. This advancement could provide critical internal temperature data for refining battery charging and discharging performance assessments and lifespan predictions, thereby optimizing battery management strategies.

The implementation of unmanned intelligent construction on the concrete surfaces of an airport effectively improves construction accuracy and reduces personnel investment. On the basis of three known common tracked vehicle dynamics models, reference trajectory planning and trajectory tracking controller algorithms need to be designed. In this paper, based on the driving characteristics of the tracked vehicle and the requirements of the stepping trajectory, a quartic polynomial trajectory planning algorithm was selected with the stability of the curve as a whole and the end point as the optimization goal, combining the tracked vehicle dynamics model, collision constraints, start–stop constraints and other boundary conditions. The objective function of trajectory planning was designed to effectively plan the reference trajectory of the tracked vehicle’s step-by-step travel. In order to realize accurate trajectory tracking control, a nonlinear model predictive controller with transverse-longitudinal integrated control was designed. To improve the real-time performance of the controller, a linear model predictive controller with horizontal and longitudinal decoupling was designed. MATLAB 2023A and CoppeliaSim V4.5.1 were used to co-simulate the two controller models. The experimental results show that the advantages and disadvantages of the tracked vehicle dynamics model and controller design are verified.

In extremely cold environments, when battery electric vehicles (BEVs) are navigating urban roads at low speeds, the limited heating capacity of the on-board heat pump system and positive temperature coefficient (PTC) device can lead to an inevitable decline in battery temperature, potentially falling below its permissible operating range. This situation can subsequently result in vehicle malfunctions and, in severe cases, traffic accidents. Henceforth, a novel battery self-heating method during driving is proposed to maintain battery temperature. This approach is ingeniously embedded within the heating mechanism within the motor driving system without any necessity to alter or modify the existing driving circuitry. In the meantime, the battery voltage can be regulated to prevent it from surpassing the limit, thereby ensuring the battery’s safety. This method introduces the dead zone into the space vector pulse width modulation (SVPWM) algorithm to form the newly proposed dSVPWM algorithm, which successfully changes the direction of the bus current in a PWM period and forms AC, and the amplitude of the battery alternating current (AC) can also be controlled by adjusting the heating intensity defined by the ratio of the dead zone and the compensation vector to the original zero vector. Through the Simulink model of the motor driving system, the temperature hysteresis locking strategy, grounded in the field-oriented control (FOC) method and employing the dSVPWM algorithm, has been confirmed to provide controllable and sufficiently stable motor speed regulation. During the low-speed phase of the China Light Vehicle Test Cycle (CLTC), the battery temperature fluctuation is meticulously maintained within a range of ±0.2 °C. The battery’s minimum temperature has been successfully locked at around −10 °C. In contrast, the battery temperature would decrease by a significant 1.44 °C per minute without the implementation of the temperature-locking strategy. The voltage of the battery pack is always regulated within the range of 255~378 V. It remains within the specified upper and lower thresholds. The battery voltage overrun can be effectively avoided.

The increasing popularity of electric vehicles presents both opportunities and challenges for the advancement of lithium battery technology. A new longitudinal-flow heat dissipation theory for cylindrical batteries is proposed in order to increase the energy density and uniform temperature performance of cylindrical lithium-ion battery packs while also shrinking their size by roughly 10%. First, a genetic algorithm is used to identify a single cell’s thermal properties. Based on this, modeling and simulation are used to examine the thermal properties of the longitudinal-flow-cooled battery pack. It is found that the best coolant flow scheme has one inlet and one outlet from the end face, taking into account the cooling effect of the battery pack and engineering viability. Lastly, thermal dummy cells (TDCs) are used to conduct a validation test of the liquid cooling strategy. Additionally, the simulation and test results demonstrate that the liquid cooling solution can restrict the battery pack’s maximum temperature rise under the static conditions of a continuous, high-current discharge at a rate of 3C to 20 °C and under the dynamic conditions of the New European Driving Cycle (NEDC) to 2 °C. In applications where the space requirements for the battery pack are quite strict, the longitudinal-flow cooling method has some advantages.

A new longitudinal flow heat dissipation theory for cylindrical batteries is proposed in order to increase the energy density and uniform temperature performance of cylindrical lithium-ion battery packs while also shrinking their size by roughly 10%. First, a genetic algorithm is used to identify the single cell's thermal properties. Based on this, modeling and simulation are used to examine the thermal properties of the longitudinal flow-cooled battery pack. It is found that the best coolant flow scheme has one inlet and one outlet from the end face, taking into account the cooling effect of the battery pack and engineering viability. Lastly, Thermal Dummy Cells (TDC) is used to conduct a validation test of the liquid cooling strategy. Additionally, the simulation and test results demonstrated that the liquid cooling solution can keep the battery pack's maximum temperature rise under the static conditions of a continuous, high-current discharge at a rate of 3C to 20 °C and under the dynamic conditions of the New European Driving Cycle (NEDC) to 2 °C. In applications where the space requirements for the battery pack are quite severe, the longitudinal flow cooling method has some advantages.