In the context of New Engineering Education, the rapid advancement of new energy vehicles (NEVs) has placed unprecedented demands on technical talent cultivation. As a core component of NEVs, the power battery and its battery management system (BMS) require sophisticated maintenance skills and innovative thinking. Traditional teaching methods in courses like “New Energy Vehicle Power Battery and Management System Maintenance” often fall short in addressing these needs due to content obsolescence, limited practical exposure, and rigid pedagogical approaches. In my teaching practice, I have explored and implemented a blended learning model that integrates online and offline elements to enhance student engagement, practical competence, and adaptability to industry trends. This article details the design, implementation, and outcomes of this blended learning approach, with a focus on the battery management system (BMS) as a critical aspect.
The course “New Energy Vehicle Power Battery and Management System Maintenance” is a cornerstone of NEV technology programs, typically offered in the fourth semester with 64 credit hours. It covers fundamental knowledge and hands-on skills related to power battery structures, performance testing, fault diagnosis, and BMS maintenance. However, traditional instruction faces several challenges: content lags behind fast-evolving BMS technologies, practical sessions are constrained by equipment and cost, teaching methods are teacher-centered with minimal interaction, and assessment systems overemphasize theoretical exams. To overcome these issues, I redesigned the course using a blended learning framework, which combines digital resources with face-to-face activities to foster a student-centric learning environment.
The blended learning design begins with clear objectives aligned with New Engineering goals and industry requirements. The knowledge objective aims for students to master the basic principles of power batteries and BMS, including structures, working mechanisms, and fault diagnosis methods. The ability objective focuses on developing practical skills in installation, debugging, detection, and repair of battery management systems. The quality objective cultivates teamwork, professionalism, and safety awareness. To achieve these, I restructured content into three modules: foundational theory, practical operations, and innovative extensions. The foundational module covers battery types, electrochemical processes, and BMS functions; the practical module involves hands-on projects like battery disassembly and BMS troubleshooting; and the innovative module introduces cutting-edge technologies such as smart BMS and real-world case studies.
Online and offline resources are crucial for blended learning. On the online platform, I uploaded instructional videos, e-lectures, animations, and supplementary materials like industry reports and research papers to facilitate self-paced learning. For instance, videos演示 BMS operation and battery charging processes help visualize complex concepts. Discussion forums and quizzes are used to promote interaction. Offline, the campus workshop is equipped with virtual simulation software and physical tools, including battery packs and BMS diagnostic devices, to mimic real-world scenarios. Partnerships with local enterprises provide校外实践 opportunities for students to engage with actual NEV maintenance tasks. Key formulas are introduced to reinforce theoretical understanding, such as the state of charge (SOC) estimation for a battery management system:
$$SOC(t) = SOC(0) – \frac{1}{C_n} \int_0^t i(\tau) d\tau$$
where \(C_n\) is the nominal capacity and \(i\) is the current. Another essential metric in BMS is the state of health (SOH):
$$SOH = \frac{C_{current}}{C_{nominal}} \times 100\%$$
These formulas are integrated into online modules and线下 discussions to bridge theory and practice. The battery management system (BMS) plays a vital role in monitoring and optimizing battery performance, so I emphasize its algorithms and故障诊断 techniques throughout the course.
The implementation of blended learning follows a three-phase path. In the pre-class phase, I assign预习 tasks via the online platform, such as watching videos on BMS architecture and completing self-assessments. Students are encouraged to explore resources on battery management system advancements. I monitor their progress and identify common difficulties, like understanding BMS communication protocols. During in-class sessions, I briefly review key points from online materials, then dive into hands-on activities. For example, students work in groups to perform BMS calibration or simulate fault scenarios using virtual labs. I facilitate discussions and provide immediate feedback. Post-class, students complete online assignments and participate in拓展 projects, such as analyzing BMS data from real NEVs or joining innovation competitions. This cycle reinforces learning and encourages continuous engagement with battery management system topics.
To evaluate the effectiveness of blended learning, I compared outcomes with traditional teaching methods. The table below summarizes performance metrics from two student cohorts over a semester:
| Metric | Traditional Teaching Cohort (n=50) | Blended Learning Cohort (n=50) |
|---|---|---|
| Average Final Exam Score | 75.2 | 85.6 |
| Practical Skill Assessment (out of 100) | 70.5 | 88.9 |
| Student Satisfaction Rate (survey-based) | 65% | 92% |
| BMS-Related Project Completion | 60% | 95% |
As shown, the blended learning cohort achieved higher scores in both theory and practice, with notable improvement in BMS-specific tasks. Student feedback indicated increased motivation and better grasp of battery management system complexities. Additionally, I used formulas to assess learning gains, such as calculating error rates in SOC estimation pre- and post-intervention:
$$Error_{SOC} = \frac{|SOC_{estimated} – SOC_{actual}|}{SOC_{actual}} \times 100\%$$
Post-course analysis revealed a reduction in average error from 15% to 5%, demonstrating enhanced technical proficiency. The battery management system (BMS) modules received particular praise for their interactive design.
Reflecting on the implementation, blended learning addresses the limitations of traditional pedagogy by fostering flexibility and interactivity. However, challenges persist, such as ensuring equitable access to online resources and maintaining up-to-date content on evolving BMS standards. To mitigate these, I regularly update digital materials with the latest industry trends, including advancements in battery management system software and hardware. The integration of formulas and hands-on exercises has proven effective in demystifying complex topics like BMS algorithms. For instance, I often derive the battery voltage model during lessons:
$$V_{bat} = OCV(SOC) + I \cdot R_{internal}$$
where \(OCV\) is the open-circuit voltage as a function of SOC, \(I\) is the current, and \(R_{internal}\) is the internal resistance. This reinforces the interconnection between theoretical concepts and practical BMS applications.
In conclusion, the blended learning approach for the NEV power battery and battery management system (BMS) maintenance course aligns with New Engineering objectives by enhancing教学 quality and student readiness for industry demands. Through a combination of online self-study, offline实践, and continuous assessment, students develop a comprehensive understanding of BMS operations and troubleshooting. Future work will involve refining the curriculum with更多 AI-driven tools for BMS simulation and expanding industry collaborations. Ultimately, this model serves as a参考 for other technical courses seeking to adapt to technological shifts and cultivate innovative talent in the NEV sector.