In the global wave of sustainable development and low-carbon transportation, new energy electric vehicles have become a core direction in the automotive industry transformation. As the “heart” of these vehicles, the performance and quality of EV power batteries directly determine the driving range, power output, and safety of the vehicles. The development of China EV battery systems typically includes stages such as design, virtual validation, sample package trial production, testing validation, small-batch production, and mass production. Trial production of EV power battery sample packages is the process of transforming designs into physical entities, enabling design and process validation while providing samples for performance, safety development, and overall vehicle function testing.
An EV power battery consists of hundreds of components, with cells connected in series and parallel to form high-voltage output units. If issues arise during the trial production assembly, such as poor contact or insulation failure, it can lead to severe problems like short circuits or fires. Therefore, quality control during the trial production process is critical. Trial production of China EV battery systems is not merely about assembling cells and parts; it is a comprehensive engineering task involving safety, precision, strength, and other aspects. Sample package trial production integrates factors such as personnel, equipment, materials, and methods, and any lapse in control can affect the final product. Thus, implementing a full-element quality control system for EV power battery trial production is essential.
Trial production of EV power batteries serves to validate new technical designs, identify potential issues, and optimize the design. It allows for a comprehensive evaluation of key indicators like energy density, power density, cycle life, and safety. Additionally, it helps refine welding parameters and other process details, estimate costs, and mitigate quality and safety risks before market launch. Consequently, EV power battery trial production is characterized by simultaneous multi-project development, complex and variable processes, and diverse work types. For instance, multiple cell products may be developed concurrently to meet market demands, increasing the complexity of quality control. The assembly process involves numerous parts with varying sequences and parameters, such as different welding settings for cells and busbars. Furthermore, trial production tasks range from new sample assembly to返修, display module production, and modifications, each presenting unique challenges.
Based on years of experience in China EV battery trial production, I have developed a comprehensive quality control method covering components, processes, workflows, personnel, tools, and fixtures. This method addresses issues like misassembly, omitted parts, welding deviations, and inadequate cleaning, which have historically led to failures such as insulation faults and short circuits. By analyzing trial production records, common problems were identified, leading to the establishment of a robust quality control system. Below, I detail the key aspects of this system, including component quality control, process quality control, procedural quality control, personnel quality control, and tooling quality control, supported by tables and formulas to summarize critical data.
Component Quality Control
In the early stages of China EV battery development, trial production often uses rapid prototyping components, which can have inconsistent manufacturing quality. To ensure reliability, several measures are implemented for component quality control.
First, component inspection is crucial. Before入库, suppliers must submit inspection reports, and quality personnel follow a standardized checklist to verify dimensions and features. For example, cell voltage differences, seal integrity, burrs on plastic parts, and fixing hole positions are checked. Key dimensions are measured to ensure conformity with design specifications. The inspection process can be represented by a quality index formula: $$ Q_i = \frac{N_c}{N_t} \times 100\% $$ where \( Q_i \) is the quality index, \( N_c \) is the number of conforming components, and \( N_t \) is the total components inspected. A \( Q_i \) value above 95% is typically required for acceptance.
Second, component cleanliness is vital for assembly quality and welding reliability. Parts like heating films, cells, and busbars are cleaned with alcohol and lint-free cloths, while machined surfaces are blown clean with compressed air to remove contaminants. The cleanliness standard can be quantified as: $$ C_s = \frac{A_c}{A_t} $$ where \( C_s \) is the cleanliness score, \( A_c \) is the clean area, and \( A_t \) is the total area. A minimum \( C_s \) of 0.98 is enforced to prevent welding issues.
Third, pre-assembly verification helps identify risks early. Components such as cells, plastic parts, and low-voltage harnesses are test-fitted to detect interferences or misalignments, reducing the need for rework. For instance, the fit between cells and plastic parts is checked for proper tolerances.
Fourth, component modification control ensures that customizations for specific trial production needs are managed effectively. Table 1 outlines common modification methods and quality assurance measures for China EV battery sample packages.
| Trial Production Requirement | Modification Method | Quality Control |
|---|---|---|
| Module with added temperature sensors | Plastic part drilling | Avoid surface damage; clean with compressed air after drilling |
| Module partition welding | Welding program change | Verify program update; monitor cell welding quality |
| Thermal runaway module with heating ceramic | Plastic part drilling; adhesive application | Prevent surface damage; ensure even adhesive application |
| Display module with aesthetic welds | Welding parameter adjustment; weld pattern change | Check weld appearance; ensure no surface contaminants |
Process Quality Control
The trial production of EV power batteries involves critical processes such as electrical component fixation, cell adhesive application, module assembly, and gap inspection. Deviations in these processes can lead to latent defects, necessitating strict controls.
For tightening processes, fasteners must be torqued to specifications to ensure sealing and fixation. Anti-error measures include using self-inspection paint markers for visual management and monitoring key bolts with dual verification. Table 2 lists torque requirements for critical locations in China EV battery assemblies. The tightening torque can be modeled as: $$ T = k \cdot D \cdot F $$ where \( T \) is the torque, \( k \) is the nut factor, \( D \) is the bolt diameter, and \( F \) is the preload force. A flowchart for tightening quality control involves initial torque application, marking, re-inspection by a second operator, and documentation.
| Assembly Location | Torque Requirement (Nm) |
|---|---|
| Module plastic support column fixing bolt | 5 ± 1 |
| Module plastic upper and lower shell screw | 3 ± 1 |
| Module metal C-bracket fixing bolt | 6 ± 1 |
| Module fixing connection nut | 10 ± 1 |
| Module high-voltage busbar fixing bolt | 8 ± 1 |
| Module fixed to lower shell bolt | 9 ± 1 |
| Main positive and negative relay fixing bolt | 8 ± 1 |
| Pre-charge relay and resistor fixing bolt | 6 ± 1 |
| High-voltage socket fixing bolt | 9 ± 1 |
| Low-voltage socket fixing bolt | 5 ± 1 |
| Fuse and shunt fixing nut | 8 ± 1 |
| High-voltage cable, M6/M8 support base fixing bolt | 8 ± 1 |
| LBC controller fixing bolt | 5 ± 1 |
| Upper shell sealing fixing bolt | 10 ± 1 |
| Vent valve plastic bolt | 1.2 ± 0.2 |
Adhesive application processes require precision to secure cells and modules. Manual application is common in trial production, but it is controlled using specialized personnel and electric dispensing guns to ensure consistent bead geometry. The adhesive volume \( V_a \) can be calculated as: $$ V_a = A_b \cdot t_a $$ where \( A_b \) is the bond area and \( t_a \) is the adhesive thickness. Quality checks include verifying continuity and thickness uniformity.
Pressing processes, such as module compaction, use custom fixtures to maintain dimensional accuracy. For example, module width must be controlled to prevent assembly issues. The pressing force \( F_p \) is determined by: $$ F_p = \frac{E \cdot A \cdot \Delta L}{L} $$ where \( E \) is the modulus of elasticity, \( A \) is the cross-sectional area, \( \Delta L \) is the deformation, and \( L \) is the original length. Fixtures are designed based on cell size and module configuration.
Gap inspection is critical for safety in China EV battery designs with dense cell arrangements. Feeler gauges and constraints like cell fixation frames are used to ensure gaps within design limits. The gap size \( g \) must satisfy: $$ g_{\text{min}} \leq g \leq g_{\text{max}} $$ where \( g_{\text{min}} \) and \( g_{\text{max}} \) are specified tolerances.
Sealing checks are performed on cooling管路 and the entire battery package to prevent leaks that could cause insulation faults. Pre-assembly and post-assembly tests include pressure decay and waterproof checks.
Procedural Quality Control
To manage the numerous factors affecting EV power battery trial production quality, optimized workflows with key control points are established. These points enable real-time issue identification and resolution.
The key quality control points in China EV battery trial production are: cell inspection, component check, module pre-assembly, cell welding, weld inspection, electrical component installation, high-voltage connection, low-voltage debugging, performance check, and sealing verification. Each point has specific inspection items. For instance, pre-assembly checks include cell voltage differentials, polarity orientation, and busbar alignment. Welding checks involve fixture stability, conduction tests, and parameter verification. Final assembly checks cover module fixation, cooling system integrity, and BMS controller condition. Delivery inspections use standardized checklists for aspects like part fixation, torque markings, and surface quality.
A multi-layer verification system is implemented: self-inspection by the operator, re-inspection by a second technician, and random audits by quality staff. This approach prevents errors, such as reversed cell polarity, from propagating. The overall quality performance can be expressed as: $$ Q_p = \prod_{i=1}^{n} (1 – p_i) $$ where \( Q_p \) is the product quality level, \( p_i \) is the defect probability at control point \( i \), and \( n \) is the number of control points. By minimizing \( p_i \), \( Q_p \) approaches 1, indicating high reliability.
Personnel Quality Control
The skill and expertise of personnel are pivotal in China EV battery trial production, where operators must be versatile and proficient.
A systematic training program is essential. New personnel undergo comprehensive training from empty cells to liquid-filled cell welding, with assessments required before role assignment. This ensures competence in handling complex tasks like laser welding and programming.
Real-time process training is conducted as designs evolve through hand-made samples, soft-tooled parts, and hard-tooled parts. Regular updates on assembly sequences and parameters keep the team aligned with changes.
Standardization of common processes, such as laser welding machine operation and package sealing checks, through documented procedures enhances consistency and efficiency across EV power battery projects.
Periodic review of trial production issues helps in root cause analysis and solution development. A problem database is maintained and shared to prevent recurrence, fostering continuous improvement. The learning curve can be modeled as: $$ T_t = T_0 \cdot N^{-b} $$ where \( T_t \) is the time per unit after \( N \) repetitions, \( T_0 \) is the initial time, and \( b \) is the learning rate. Regular复盘 accelerates this curve, reducing errors over time.
Tooling and Fixture Quality Control
Tools and fixtures significantly impact the quality of EV power battery trial production, particularly in processes like welding and pressing.
Regular inspections are mandated using checklists to identify wear or damage. A loan tracking system manages external tool usage, ensuring accountability.
Critical parameters, such as laser welding mirror power, degrade with use and require periodic calibration or replacement. The degradation rate \( d \) can be described as: $$ P = P_0 \cdot e^{-d \cdot u} $$ where \( P \) is the current power, \( P_0 \) is the initial power, and \( u \) is the usage cycles. Maintenance schedules are based on this to sustain performance.
Fixtures are improved iteratively to match process refinements. For example, cell screening fixtures evolved from single-slot designs to cylindrical ones that align poles and vent holes simultaneously, enhancing accuracy. The improvement in fixture effectiveness \( E_f \) can be quantified as: $$ E_f = \frac{N_{c}}{N_{t}} \cdot 100\% $$ where \( N_{c} \) is the number of correctly oriented cells and \( N_{t} \) is the total cells processed. Upgrades have shown \( E_f \) increases from 90% to over 98%.
Conclusion
In summary, based on extensive experience in China EV battery trial production, I have outlined a holistic quality control method for EV power battery sample packages. This approach encompasses component quality, process rigor, procedural checks, personnel development, and tooling management. By integrating elements such as component inspection, cleanliness assurance, adhesive application, gap control, and multi-layer verification, a full-element quality control system is established. This system not only mitigates risks but also enhances the reliability and safety of EV power batteries, supporting the advancement of electric vehicles globally. The use of tables and formulas provides a structured way to monitor and improve quality, ensuring that trial production meets the high standards required for successful product development.