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This paper analyzes the current control, mode control and boost strategy of permanent magnet synchronous motor in dual hybrid system, which has good stability and robustness. Current control includes current vector control, MTPA control, flux weakening control, PI current control and SVPWM control. Motor mode includes initialization mode, normal mode, fault mode, active discharge mode, power off mode, battery heating mode and boost mode. The boost strategy of the hybrid system is based on boost mode management, boost target voltage determination and boost PI control. The specific content is as follows: Boost mode control. Boost mode includes initial mode, normal mode, off mode and fault mode. Boost target voltage is determined. Boost converter is controlled by variable voltage, which depends on the operation status of the motor and generator..

The collision accidents of electric vehicles are gradually increasing, and the response of battery cell under mechanical abuse conditions has attracted more and more attention. In the real collision, the mechanical load on battery generally has the following characteristics, including multiple loading directions, dynamic impact and blunt intrusion. Therefore, it is necessary to study the mechanical response and deformation of battery under complex loading, especially in-plane dynamic loading condition. According to the actual accident, we designed the constrained blunt compression test of the battery in different speeds and directions. For out-of-plane loading, the structural stiffness of battery increases obviously and the fracture is advanced compared with the corresponding quasi-static tests. For in-plane constrained loading, the force response can be approximately divided into two linear segments, in which the structural stiffness increases abruptly after the inflection point.

In order to realize the series-parallel switching control of hybrid electric vehicle (HEV) with dual-motor hybrid configuration, a method of unpowered interrupt switching based on the coordinated control of three power sources was proposed by analyzing the series-parallel driving mode of the dual-motor hybrid configuration. The series to parallel switching process is divided into three stages: speed regulation stage, clutch combination and power source switching. The distribution control of speed regulating torque is carried out in the speed regulating stage. The speed adjustment torque is preferentially allocated to the power source of the input shaft (engine and P1) to carry out the lifting torque. Due to the high speed adjustment accuracy and fast response of the P1 motor, the input shaft is preferentially allocated to P1 for speed adjustment, that is, the torque intervention of P1.

In order to achieve seamless mode switching control for hybrid electric vehicles (HEVs) in the event of battery failure, we propose a motor voltage-controlled mode switching method that eliminates power interruptions. This approach is based on an analysis of the dual-motor hybrid configuration's mode switching. We analyze the overall vehicle operation when the high-voltage battery occurs in different hybrid modes. To ensure that the vehicle can still function like a conventional car under such circumstances, we introduce a novel "voltage control" mode. In this mode, instead of operating in its traditional torque control manner, the P1 motor adopts a voltage control strategy. The P1 controller's variable becomes "voltage," and VCU sends the motor's working mode switching request and PCM finishes the mode transition. During system operation, the P1 motor promptly responds to these target voltages to maintain bus voltage within a normal range.

Due to the objectives of achieving high fuel efficiency and drivability performance, a dual-drive hybrid system with two motors has been developed. Various drive modes are presented based on engine status, requested driver torque and power, as well as C0 status in different working conditions. The transition control of drive mode change poses a unique challenge for the dual-drive hybrid system. This study discusses the control strategies for transitioning between drive modes. The first type of transition mode is divided into four distinct phases. In the second mode transition, there are three phases: the synchronization phase involving P1 torque intervention, the C0 lock-up phase involving frozen P1 torque control and adjustment of C0 clutch torque and pressure correlation, and finally, the torque exchange phase. The third type of transition includes a dedicated torque transition phase followed by a C0 disengaged phase and concluding with a speed synchronization phase.

To characterize emission performance and engine operating conditions during high-power cold starts (HPCS), a blended plug-in hybrid electric vehicle was tested over worldwide harmonized light-duty vehicle test cycle (WLTC), and a new cycle was developed to characterize HPCS. The results showed that the engine speed and load increased dramatically to high level during HPCS under the low temperature of coolant and catalysts. The higher concentration of particle number (PN) and NOx at higher speed and load, accounted for the higher emissions during HPCS. Besides, the cumulative PN emissions increased first and then decreased with the increasing coolant temperature.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

In order to obtain a good understanding of mechanical behaviors of lithium-ion battery modules in electric vehicles, comprehensive experimental and numerical investigations were performed in the study. Mechanical indentation tests with different indentation heads, different loading directions and different impact speeds were performed on battery modules with prismatic cells. To mitigate thermal runaway, only fully discharged battery modules were used. The force-displacement responses and open circuit voltage were recorded and compared. It was found that the battery modules experienced different failure modes when subjected to mechanical abuse. Besides internal short circuit of cells, external short circuit from bus bar and vapor leakage of electrolyte were also found to deteriorate the mechanical and electrical integrity of the tested modules. Mechanical anisotropy and dynamic effect were found on the battery module.

In this decade, the detailed multi-layer FE model is always applied for investigating the mechanical behavior of Li-ion batteries under mechanical abuse. However, establishing a detailed model of different types of batteries requires a series of material characterization of components. To improve the efficiency of the procedure of component calibration, we introduce a procedure of automatic coating material characterization as an example to represent the strategy. The proposed method is constructing a response solver through MATLAB to predict the mechanical behavior of the coating specimen's representative volume element (RVE) under designated test conditions. The coating material is represented through Drucker-Prager-Cap (DPC) model. All parameters, including boundary conditions and material parameters, are included in this solver.

This work presents a multi-objective adaptive cruise control (ACC) system via deep reinforcement learning (DRL). During the control period, it quantitatively considers three indexes: tracking accuracy, riding comfort, and fuel economy. The system balances contradictions between different indexes to achieve the best overall control results. First, a hierarchical control architecture is utilized, where the upper level controller is synthesized under DRL framework to give out the vehicle desired acceleration. The lower level controller executes the command and compensates vehicle dynamics. Then, four state variables that can comprehensively determine the car-following states are selected for better convergence. Multi-objective reward function is quantitatively designed referring to the evaluation indexes, in which safety constraints are considered by adding violation penalty. Thereafter, the training environment which excludes the disturbance of preceding car acceleration is built.

Batteries have various sizes and can be configured into different layouts in battery pack on electric vehicles. Crash safety performance is one of the key requirements in choosing battery geometric characteristics and designing layout of battery cells in battery pack. In this study, we compared impact responses of different configurations and geometric characteristics of battery cells under side pole impact. The side pole impact is a relatively dangerous collision type for electric vehicles, often causing large deformation and damage to the battery. Using a production battery pack, we first conducted side pole impact tests with sled tester, and then simulated the test configuration.

To satisfy the power and energy requirement of the systems, such as electrical vehicles, the battery packs are constructed with hundreds of single cells connected in series and parallel connection. The most significant difference between a single cell and a battery pack is cell-to-cell variation. Not only does cell-to-cell variation have a big effect on the available energy and power of the battery packs, but also it causes early degradation of battery and potential safety issues. The cell variation effects on battery packs are widely studied because it is of great significance for battery sorting and management scheme. In this paper, battery pack inconsistency is clearly defined and the resulting battery capacity loss and aging acceleration problems are analyzed in detail. A comprehensive LiFePO4 battery pack model was established, which has taken into account cell-to-cell variation, thermal model, capacity degradation, resistance increasing and different battery topologies.

In order to get a better understanding of the mechanical behavior of lithium-ion battery cells, especially for the mechanical anisotropy and dynamic effect, a series of tests for quasi-static indentation and dynamic impact tests has been designed. In the study, mechanical indentation tests with different indentation heads, different loading directions and different impact speeds were performed on a type of large format prismatic lithium-ion battery cells and jellyrolls of them. To mitigate thermal runaway, only fully-discharged cells and jellyrolls were used. The force-displacement response and open circuit voltage (OCV) were recorded and compared. It shows that jellyroll and battery cell have apparent mechanical anisotropy and strain-rate effect. The stiffness of jellyroll and cell in out-of-plane direction is much larger than that in two in-plane directions.

Plug-in electric vehicle (PHEV) has a promising prospect to reduce greenhouse gas (GHG) emission and optimize engine operating in high-efficiency region. According to the maximum electric power and all-electric range, PHEVs are divided into two categories, including “all-electric PHEV” and “blended PHEV” and the latter provides a potential for more rational energy distribution because engine participates in vehicle driving during aggressive acceleration not just by motor. However, the frequent use of engine may result in severe emissions especially in low state of charge (SOC) and ahead of catalyst light-off. This study quantitatively investigates the impact of oil viscosity and driving mode (hybrid/conventional) on oil dilution and emissions including particle number (PN).

In the past two decades, rapidly expanding economy in China led to burst in travel demand and pursuit of quality of life. It further promoted the rapid growth of China's passenger car market. China had already become the largest vehicle sales country, exceeding the U.S. in 2010. By the end of 2018, there had been over 240 million cars in China, with over 200 million passenger cars. The surge of car ownership has also brought a series of problems, like traffic congestion, long commuting time, insufficient parking space, etc. Therefore, some local governments in China introduced vehicle purchase restriction policies to control the growth and gross of vehicle stock. Different cities issued different rules. Lottery and auction mechanisms both exist. There are also differences in classification and licensing of electric vehicles. However, with the recent slowdown of economic development, China's car sales began to decline in 2018, and the trend of 2019 is also not optimistic.

Automated parking is an efficient way to solve parking difficulties and path planning is of great concern for parking maneuvers [1]. Meanwhile, the starting region of path planning greatly affects the parking process and efficiency. The present research of the starting region are mostly determined based on a single algorithm, which limits the flexibility and efficiency of planning feasible paths. This paper, taking parallel parking and vertical parking for example, proposes a method to calculate the starting region and select the most suitable path planning algorithm for parking, which can improve the parking efficiency and reduce the complexity. The collision situations of each path planning algorithm are analyzed under collision-free conditions based on parallel and vertical parking. The starting region for each algorithm can then be calculated under collision-free conditions.

Batteries are exposed to dynamic load during vehicle driving. It is significant to clarify the load input of the battery system during vehicle driving for battery pack structural design and optimization. Currently, bolt connection is mostly applied for battery pack constraint to vehicle, as well as for module assembly inside the pack. However, accurate bolt load is always difficult to obtain, while directly force measurement is expensive and time consuming in engineering. In this paper, a precise data driven model based on Elman neural network is established to identify the dynamic bolt loads of the battery pack, using tested acceleration data near bolts. The dynamic bolt force data is measured at the same time with the acceleration data during vehicle running in different driving conditions, utilizing customized bolt force sensors.

The crash safety of lithium-ion batteries has received great attention in recent years because of their growing popularity in electric vehicles. However, the safety issues of prismatic batteries have not been thoroughly studied; in particular, the mechanical responses of prismatic battery cells with lateral constraints under varied loading conditions still remain unclear. In this study, indentation tests are conducted to study the mechanical response of prismatic battery cells. Fixtures providing lateral constraint which simulates the real packing situation in battery module are designed. Firstly, the effects of lateral constraints on coupled mechanical and electrical responses of prismatic battery cells are analyzed and discussed. Secondly, dynamic indentation tests of prismatic cells with lateral constraints are carried out. The response of the stacked batteries under local loading is revealed.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

Fuel cell vehicle and battery electric vehicle are two environmentally benign vehicle technology types possibly meeting the zero-emission regulations in the future. The premise is they can achieve parity with conventional vehicle both environmentally and economically. Besides, it is necessary to distinguish which technology is more suitable in China's current and future context. This paper compares their cost-effectiveness for reducing greenhouse gas emissions, examining the life-cycle greenhouse gas emissions of conventional gasoline vehicle, battery electric vehicle and fuel cell vehicle in China's energy context under three different scenarios. The results indicate that under the 500km drive range, fuel cell vehicles are less competitive than battery electric vehicles currently. Fuel cell vehicles generate much more greenhouse gas emissions than battery vehicles and conventional gasoline vehicles.